Life

Throughout history, our species has devoted much thought, research, and debate in the enterprises of determining the fundamental nature of living systems, and explaining their origin and diversity &mdash; in short, in attempting to define life. At any given time in history, the prevailing answers to the perennial question, "what is life?", depended on the extent of human knowledge at the time, and to the interpretations given that knowledge, as well to belief systems based on religious-type faith. At this writing late in the first decade of the 21st century, that still remains the case.

From the perspective of early 21st century scientific knowledge, we focus in this article on the essential activities that living systems perform to enable their living &mdash; specifically, we focus on the fundamental processes of living, those that constitute a system that counts as a living system, the "common denominator [or denominators] that allows for the discrimination of the living from the non-living", as inferred from the study of Earth's living systems in the light of modern science.

We take as our theme the definition of life given by Nobel prizewinning cellular/molecular biologist, Christian De Duve: "Life is what is common to all living beings". Those commonalities include the basic chemical constituents of living system; the fundamental working unit and building block of life, the biological cell &mdash; the 'atoms' of living systems &mdash; and the many molecular and supramolecular structures, interrelationships and interactions cells have in common, including a boundary that both isolates it from its external environment and enables it to exchange matter, energy, and information with it to maintain the activities of living; the importation of energy and its application in performing cellular work; the exportation of more disorder than the order it generates within itself; metabolism; information processing and communication; self-assembly and self-organization and self-defense; homeostasis; allostasis and adaptation; emergent behavior; reproduction; cognition of self and the world outside the self; and, death.

In stating that Life is what is common to all living beings, De Duve explains: This answer is not a tautology, as it allows many attributes to be excluded from the definition of life….What remains is what we humans have in common with the colibacilli in our gut. It is still a lot….We and colibacilli, together with all other living beings, are made of cells, which are constructed with the same substances. We build our constituents by the same mechanisms. We depend on the same processes to extract energy from the environment and convert it into useful work. Most telling of all, we use the same genetic language, obey the same code. There are differences, of course. Otherwise, we would all be identical. But the basic blueprint is the same. There is only one life…..We and colibacilli are distant cousins; very distant, but indubitably related.

What is Life?
Biologists use the word life in several of its many senses, to refer to:
 * the biography of a living thing &mdash; the life of a mountain gorilla &mdash; its life history &mdash; sometimes even after it/she/he has died &mdash; the life of Albert Einstein;


 * a way of living &mdash; she led the life of an artist;
 * living things in the aggregate &mdash; plant life, marine life;
 * the relationships among living things &mdash; the life of the forest;
 * biology-related sciences &mdash; she became a life scientist, specializing in plant physiology;
 * intellectual or imaginative activity &mdash; the life of the mind;
 * all of the living things past and present &mdash; evolution of life; and,
 * the shared fundamental processes that characterize living things and that distinguish them from non-living matter &mdash; life as a unique self-fabricating material system.

Biologists use the latter sense of ‘life’ when asking "what is life?" and "what is the origin of life?"

Perhaps elsewhere in the universe we might find the same kinds of processes that characterize living things on Earth, or, foregoing geoanthropocentrism, we might find different kinds of processes generating entities that we might recognize as living. In this article, for life on Earth only, can we make observations and draw a few provisional conclusions to the question, "what is life?".

Science can conceive that non-living matter could acquire naturally those processes that characterize living things. If living things developed from inanimate things, as science postulates, can we discover how that happened? We leave that question for an origin of life article. Here we focus on discovering the shared fundamental processes that uniquely characterize living things (on Earth), those elementary processes that origin-of-life researchers would need to know in order to target their search for the mechanisms that led to the transition of the non-living to the living.

Building blocks
Whether matter has substance or not, biologists usually consider the structural basis of living system as atoms and their bonds with each other as molecules and supramolecular complexes. On Earth, everything living teems with vibrating and jostling molecules of myriad types and sizes, too small for the naked human eye to see, but numerous enough to manifest themselves, transmogrified, as a flea or a giant sequoia tree, the latter of which may consist of up to 4.5 million pounds of molecules. It inspires wonder that as particular collections of molecules, we humans can generate words shaped into metaphors that attempt to explain the very activity of living that enables that feeling of wonder. Notwithstanding the molecular foundation of living things, the atoms and molecules must first self-aggregate and self-organize as biological cells before anything living can emerge.

Science consider cells the units of life (life's atoms, so to speak). Living organisms can exist either as single cells or as communities of interacting cells. In living cells, organic molecules exist in heterogeneous pools of colloidal aqueous solutions bounded by lipid-protein-carbohydrate membranes (e.g., nuclei, mitochondria, endoplasmic reticulum (see Cell). Each pool can have a different composition with distinct properties (e.g., transmembrane electrical potential difference; density; viscosity; osmotic pressure; acidity; ionic strength) and different orderly arrangements of parts. This heterogeneity provides the basis for the physiology that can cause electric fields, fluid shifts, energy transfers, within-cell and between-cell communication, and the transport of molecules into and out of the pools.

Although organic molecules contain a variety of atomic elements (especially hydrogen, oxygen, nitrogen, phosphorus, and sulfur), they always have a predominant structure of carbon atoms, typically linked as carbon-to-carbon bonds in diverse topologies. All cells share a common set of carbon-containing molecules - organic molecules, dissolved or dispersed in water as a common medium of housing and interaction &mdash; water comprises ~60-70% of the mature human organism. Those molecules include relatively small molecules, like amino acids, nucleotides, monosaccharides, and esters, and large macromolecules made up of sequences of smaller organic molecules. Organic macromolecules include proteins (sequences of amino acids), lipids, nucleic acids (sequences of nucleotides), polysaccharide (sequences of monosaccharides), and many other molecular genera.

We find the 'stuff' of life, then, in carbon-to-carbon chains, studded with other chemical elements, arranged in aqueous lagoons containing a variety of organic and inorganic molecules, interacting in accord with physico-chemical principles.

&mdash; Molecules

 * See related topics: Chemistry, Biochemistry, and Organic Chemistry

Why do carbon atoms play a central role in the chemistry of living things? The answer emerges from the details of the physical chemistry of carbon. Carbon has four electrons in its outer shell, which has a capacity to hold eight electrons. The atom behaves as if it seeks four additional electrons to fill its outer shell to its capacity (see accompanying figure and caption). Metaphorically speaking, it usually achieves its goal by forming "covalent bonds" with other atoms, sharing electrons with other atoms also behaving as if they each sought to fill their outer shell. Thus, the physical chemistry of carbon enables it to bond with many other elements with unfilled outer shells. Those include hydrogen, which can share one electron with carbon to fill its [hydrogen's] outer shell, allowing carbon to covalently bond to four hydrogen atoms, as in methane (CH4) [=natural gas]; oxygen, which can share two electrons with carbon to fill its [oxygen's] outer shell, allowing carbon to double-covalently bond with two oxygen atoms, as in carbon dioxide (CO2, or O=C=O; and nitrogen, which can share three electrons with carbon to fill its [nitrogen's] outer shell, allowing carbon to triple-covalently bond with one nitrogen atom, as in hydrocyanic acid (HCN). Most importantly, carbon can share electrons with itself, allowing the formation of C-C bonds, including double bonds (C=C) and triple bonds. The avidity for carbon to bond to itself allows carbon atoms to join into long chains, sometimes with C-C side chains, or even closed rings of C-C bonds, with or without side chains. Rings and chains and branches of linked carbons can combine into almost any imaginable shape. The particular covalent bonding capacity of carbon thus enables it to combine with hydrogen, oxygen, nitrogen, and itself in multi-varied ways that generate small carbon-based molecules such as sugars, amino acids and nucleotides, which can join to become huge macromolecules with remarkable stability. The sequences of the varied subunits of such macromolecules, and the particular three dimensional shapes those sequences enable, give them the informational content required for self-assembling the dynamic organization of cells, for metabolic functioning, and for constructing copies of themselves.

The variety of carbon bonds vary in strength as well as in 3-D conformation. The simplest set of bonds that carbon can form is that of a tetrahedron, or pyramid, but the capacity of carbon for single, double and triple covalent bonding allows for many different geometries. Changing from one type of C-C bond to another type, as when a double bond is reduced to a single bond, will cause energy changes but without destroying the molecule. Such changes not only affect the molecule's energy state, but also affect the shape of the molecule and the particular side groups attached to it. One might say that the 'pulse of life' is represented at an atomic level.

The properties of carbon mean that organic macromolecules can contain huge 'banks' of information coded in their structure. Not only can each of the constituent molecules be huge, but several categories of chemicals, like nucleotides or amino acids, that contain several different species, can be ordered so that the possible combinations are effectively limitless. All of these molecules are involved in the molecular-interaction networks of cells.

Amongst those networks of molecular interactions are those that enable cells to import and transform energy and energy-rich matter from the environment and that ultimately enable cells to grow, survive and reproduce. Matter needs energy to vitalize it. D'Arcy Thompson, a pioneering biologist in the early 20th century, considered talking about molecules (or matter generally) only provides convenience in that enables us to abbreviate the nomenclature and description of the energies and their forces that give the molecular assembly living status.

Elsewhere in the universe, elements other than carbon and Earth-life's carbon-associated elements might give structure to living systems. Silicon, carbon's close columnar relative on the periodic table, also forms bond-chains with itself, forms covalent bonds with other elements, and supplies the basis for extraterrestrial living systems in fantasies by science fiction writers. Scientists conclude that silicon-silicon bonds do not stabilize under an Earth-like physico-chemical environment compatible with life as we know it. Living systems, whether carbon-based or not, may not even require water to support the organization's chemistry.

Some physicists and science writers propose that extraterrestrial life may develop based on inorganic matter or even non-molecularly based systems.

&mdash; Cells

 * See Related Topics: Cell, Microbiology, Systems biology

In recognizing a living thing, biologists recognize it as a unity within an environment, yet apart from it &mdash; a compartment of a larger whole, structurally distinguishable though not functionally completely isolated from or closed to its surroundings. Every entity that biologists acknowledge as living &mdash; bacteria, trees, fish, chimpanzees &mdash; has a structurally compartmentalized building block, the biological cell. All cells extend themselves to (and include) an enclosing boundary that consists of a lipid-protein molecular membrane known as the cytoplasmic membrane, which structurally separates the interior of the cell from the external environment while allowing certain exchanges of energy and matter. The lipid molecules form the backbone of the cell membrane.

Many organisms live as isolated cells, others as cooperative colonies of cells, and still others as complex multicellular systems that include diverse cell types, each specializing in different functions. Nature has produced an enormous variety of cell types that span three vast ‘domains’ of living systems: Archaea, Bacteria, and Eukarya, yet cells in all three domains have many features in common. In particular, as described above, they have a surrounding membrane, a physical boundary that separates them from their environment. (Yet that generally accepted commonality may oversimplify: see )

The detailed composition of cell membranes differ among cell types, with differing protein types and auxiliary lipid species, enabling specific kinds of functional exchanges with the surroundings. Pores, receptor molecules and protective walls are often features of the cell surface, in both unicellular and multicellular entities.

Current evidence indicates that only pre-existing cells can ‘manufacture’ cells, so how did the first cell(s) arise? Examining what all cells have in common may provide insight to the origin of life. All extract energy from energy-rich molecules by simple oxidation reactions, and convert it into other, chemical forms of energy useful for cell function. The molecule ATP universally serves as the cell's main energy 'currency'. All cells inherit digitally stored information in the form of molecules of DNA, and with minor exceptions the DNA of all cells use the same universal genetic code to guide production of a myriad of distinct protein structures. Cells use those proteins to carry out diverse activities, including energy processing and conversion of carbon, nitrogen and phosphorous-containing materials into cellular structures. In the human genome, perhaps as few as 22,000 different protein-coding genes lead to the production of many times more distinct protein structures that make up the variety and quantity of protein molecules needed for the structures and functions of a cell. Numerous molecular mechanisms account for that quantitative gene-to-protein amplification.

Nature has produced a huge diversity of single-celled organisms and complex animals and plants. These can contain vast numbers of cells, each part of a specialized subpopulation (cell types) &mdash; in a mammal, the cells that make up bone differ in numerous structural and functional properties from those that make up muscle, and differ again from those that make up skin, for example. Humans contain approximately 200 different cell types as classified by microscopic anatomy. In multicellular organisms, cells combine to make organs, the functional and structural components of the single larger organism.

What makes a single celled organism 'alive', and does the answer apply also when we call a large complex multicellular animal or plant 'alive'? What exactly do we mean by 'living'? We turn to those considerations next.

The thermodynamics of 'living'

 * See also: Signed Article by John Whitfield: Survival of the Likeliest? — Using the laws of thermodynamics to explain natural selection — and life itself

Biologists have learned the importance of viewing living things from the perspective of thermodynamics &mdash; the science of interactions among energy, heat, work, and entropy (the degree of disorder of a system) and information (the degree of order of a system). These interactions define what a system can and cannot do when interconverting energy and work. For example, by the First Law of Thermodynamics, when a process converts one form of energy (e.g., light) to another (e.g., electricity), no net loss of energy and no net gain results, when the byproduct, heat, is taken into account. Once heat gets generated in an energy conversion, it becomes difficult to reverse the conversion. We can use sunlight to generate light back having a solar cell power a lightbulb, but do not get all the light back because some of the energy of sunshine converts to heat &mdash; i.e., it gets degraded to a lower 'quality' form of energy, less organized.

Scientists developed the laws of thermodynamics through experiment, debate, mathematical formulation and conceptual refinement; Albert Einstein believed that they stood as an edifice of physical theory that would never topple.

The Second Law of Thermodynamics has fundamental pertinence to the understanding of living systems:


 * Heat flows spontaneously &mdash; i.e., without help from an external agency &mdash; from a region of higher temperature to one of lower temperature, and never spontaneously in the reverse direction. That also holds for other forms of energy, including electromagnetic and chemical energy: concentrations of energy disperse, down-flow, to lower energy levels, flowing, so to speak, "into the cool", and in the process, capable of doing work.
 * When heat, as input to a system, causes it to perform work (e.g., as in a steam engine), it never converts the energy input entirely to work. Some of the heat always dissipates as ‘exhaust’, lower quality heat energy unusable by the system for further work. That also holds for other forms of energy doing work; some of the energy always turns into exhaust, typically heat.  As empirical fact, conversion of energy to work in a system can never proceed at 100% efficiency.
 * Consequences arise because work can produce order in a system, but always exports some of the energy input as a less organized form of energy, heat. Experiments reveal the balance sheet of order: the degree of order of a system (e.g., a living cell) and its surroundings together never increases when energy input causes the system to perform work; the 'net' order always decreases &mdash; disorder increases. Scientists have learned how to quantify the degree of disorder, and they refer to that quantity as entropy. Water vapor, with its molecules distributed nearly randomly, has a higher entropy (the molecules show a less ordered arrangement) than liquid water, with its molecules distributed less randomly, and a much higher entropy than ice, with its molecules distributed in a more ordered crystal-like array. Left to itself in an isolated system, ice tends to spontaneously melt and liquid water to evaporate. Order tends to disorder, with the Universe as a whole tending to exhaust itself into an ‘equilibrium’ state of randomness.

Water vapor in a glass jar, with its higher degree of disorder than it would have if it were liquid water in the jar, will, at room temperature, eventually settle at the bottom of the jar into a puddle of the more ordered liquid water. That decrease in disorder (entropy) of the jar-system can occur only because the water-vapor-filled jar-system is not an isolated system, closed off from energy exchange with its surroundings. The water-vapor-filled jar can export heat to the lower-temperature room as the water vapor condenses into liquid water, releasing the heat energy that maintained the water as vapor instead of liquid &mdash; an instance of energy flowing downhill, dissipating itself from a more to a less concentrated state. The exported heat, no longer a concentrated source of energy in the water vapor, becomes a less concentrated source of energy, distributed throughout the room, the jar-system's surroundings. Because experience has established that a system and its surroundings can statistically never spontaneously increase its degree of order &mdash; according to the Second Law of Thermodynamics, the room then becomes more, or minimally as much, disordered as the jar-system became more ordered. Thus, an open system can become more ordered spontaneously without conflict with the Second Law of Thermodynamics.

The above three expressions of the Second Law of Thermodynamics reflect the fact that energy and order spontaneously flow downhill &mdash; down a ‘gradient’&mdash; toward eliminating the gradient of energy. Upon eliminating the gradient by flowing downhill, no energy flows, all work production ceases, all order dissipates, and an equilibrium state of maximal disorder, entropy, ensues.

So, how do living entities, those manifestly energized organisms, come into existence &mdash; to develop from an embryonic state to one of more order and less entropy &mdash; and perpetuate their order? How do they thwart the Second Law of Thermodynamics?

They don’t: they only seem to do so. We saw, in the jar-filled water vapor example, that an 'open' system &mdash; one that can exchange energy with its surroundings &mdash; can order itself within the constraints of the Second Law of Thermodynamics. Living systems exploit the Universe’s gradients of energy and order. Like a steam engine, they 'import' energy and order, convert it to the work of building internal order in the form of a dynamic organization of constituent elements, which they fabricate themselves, and so fabricate a system of decreasing internal (within-system) entropy. But, all along, they emit enough 'exhaust' to increase the disorder and entropy of their surroundings, so that the total entropy of the living system and its surroundings increases. Thereby the Second Law receives its due. The living system skims off a portion of the order flowing past it; it ingests order.

Biological cells qualify as non-equilibrium thermodynamic open systems, appropriating some of the energy flowing past them, using it to keep away from the equilibrium state of randomness dictated by the Second Law. By exporting unusable energy as heat, they actually export more disorder (entropy) than they produce within themselves, thereby increasing the total entropy of the universe. They hasten the dissipation of the energy gradient they are in, as if nature's abhorrence of energy gradients 'favored' the origin, development and persistence of living systems to maximize the rate of entropy gain of the Universe as a whole.

Importantly, living things can store energy.

Recognition of the need for energy, as defined by the physicists, to enable life, has a long history.

A living system always works far from the 'equilibrium' state of activity that would ensue if no energy could be imported, and energy from outside keeps the system far from equilibrium. Non-equilibrium thermodynamic open systems, including living things, can exhibit unexpectedly complex behaviors because of their far-from-equilibrium state, and one very remarkable behavior that can result is self-organization.

The sun (Sol) supplies much of the energy gradient that sources thermodynamic disequilibrium for living systems on earth. However, as Benner et al. point out,

...heavier atomic nuclei, left from a supernova, are not at thermodynamic equilibrium. Decay of these nuclei is a powerful source of planetary not-at-equilibrium environments. Radioactive decay [deep in Earth] drives tectonics and volcanism on Earth. These create non-equilibrium environment in many areas such as black smokers on the ocean floor. The consequent energetic disequilibrium supports life [near them] despite the absence of direct solar energy.

Some biophysicists propose that the production of order by matter in an energy gradient, as in living things, tends to develop inevitably and proceed inexorably. They give two reasons: (1) the production of order through work, by exporting more than counterbalancing degrees of disorder, increases total entropy production (i.e., dissipates the energy gradient and renders the dissipated energy unusable) beyond that which would otherwise occur, and (2) energy sources dissipate their gradient to produce disorder at the fastest rate possible &mdash; to reach random thermal equilibrium as fast as they can. In other words, the physical principles governing energy gradient dissipation and energy degradation not only allows the development of living systems, but, in effect, tends to select for them &mdash; or urges their emergence &mdash; in particular, when no constraints are present disallowing their development (e.g., excess heat, poverty of appropriate resources. See additional argument in:

Thermodynamic principles thus contribute not only to answering the question “what is life?” but also to “why is there life?”. Sir Arthur Eddington, the astronomer who first confirmed Albert Einstein's general theory of relativity, remarked:

The law that entropy always increases--the second law of thermodynamics--holds, I think, the supreme position among the laws of Nature. If someone points out to you that your pet theory of the universe is in disagreement with Maxwell's equations--then so much the worse for Maxwell's equations. If it is found to be contradicted by observation--well, these experimentalists do bungle things sometimes. But if your theory is found to be against the second law of thermodynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation.

Harold Morowitz and Eric Smith begin their essay on that perspective as follows:

Life is universally understood to require a source of free energy and mechanisms with which to harness it. Remarkably, the converse may also be true: the continuous generation of sources of free energy by abiotic processes [e.g., energy from radioactive decay deep in the Earth] may have forced life into existence as a means to alleviate the buildup of free energy stresses. This assertion &mdash; for which there is precedent in non-equilibrium statistical mechanics and growing empirical evidence from chemistry &mdash; would imply that life had to emerge on the earth, that at least the early steps would occur in the same way on any similar planet, and that we should be able to predict many of these steps from first principles of chemistry and physics together with an accurate understanding of geochemical conditions on the early earth. A deterministic emergence of life would reflect an essential continuity between physics, chemistry, and biology. It would show that a part of the order we recognize as living is thermodynamic order inherent in the geosphere, and that some aspects of Darwinian selection are expressions of the likely simpler statistical mechanics of physical and chemical self-organization.

See also commentary on Professors Morowitz and Smith's article.

Morowitz and Smith think that such order happens because it is a better 'lightning conductor' for discharging excess energy.

High energy (low entropy) cannot contain itself. When it has a channel to a lower energy (higher entropy) source, it discharges itself through the channel, causing patterns in space-time. Living systems provide such a channel for free energy from the sun and hydrothermal vents, because they actively consume energy and use it, in part to lower their own entropy, through growth and development and maintaining the living state. The system's surroundings receives the fruits of its labors, waste, translated as less usable energy than it would have without part of it already used up, and more entropy than without the lowering of entropy in the living organization because lowering entropy through incomplete conversion of energy to work generates entropy as waste. Living systems help relieve solar and volcanic pent-up energy, hastening its dissipation, justifying their cognomen as "dissipative structures".

We can, then, view a living system as a state of organizational activity maintained by importing, storing and transforming energy and matter &mdash; into the work of fabricating structures needed to sustain that state. They can only do so by producing waste and exporting it, and this lowers the ordered state of the environment. A living system maintains its organization at the expense of its external environment, leaving the environment more disordered than the gain in order of the living system &mdash; in keeping with the Second Law of Thermodynamics. Thus, from a thermodynamic perspective:

However, as physicist Philip Nelson writes: "The pleasure, the depth, the craft of our subject lie in the details of how living organisms work out the solution to their challenges within the framework of physical law." [Emphasis in original] To discuss those details would require invoking the facts and theories of biological physics, molecular and cell physiology, and systems biology, beyond the scope of this article if not the scope yet of those disciplines.

Metabolism
Broadly specified, metabolism encompasses the combined results of all of the body´s chemical reactions and interactions that enable living:


 * those that manage the energy exchanges of the living system, including capturing energy from outside the system, converting and inter-converting it to a variety of forms for differing physiological activities, and disposing of non-utilizable energy waste outside the system;
 * those that manage the dynamic architectural and functional status of the system through molecular reactions, for signalling, synthesis, and degradation; and,
 * those that manage disposal of waste molecular material;

&mdash; in short, the combined results of all of the body´s chemical reactions and interactions that manage persistence of the living system as a dynamic functioning entity, in particular functioning to support a self-assembling, self-organizing, developing, adapting, self-reproducing entity.

Some definitions seem to synonymize metabolism and the activity of living: ....inclusive term for the chemical reactions by which the cells of an organism transform energy, maintain their identity, and reproduce. All life forms—from single-celled algae to mammals—are dependent on many hundreds of simultaneous and precisely regulated metabolic reactions to support them from conception through growth and maturity to the final stages of death. Each of these reactions is triggered, controlled, and terminated by specific cell enzymes or catalysts, and each reaction is coordinated with the numerous other reactions throughout the organism.

Can biology encompass living systems solely in terms of metabolism? Does'metabolism' capture all of the activities common to living systems and essential to their activity of living? If so, we must include in metabolism all of the physics and chemistry enabling self-assembly, self-organization, homeostasis, allostasis, network regulation, gene regulation, and much more. Does 'metabolism' adequately describe the phenomenon of emergent behavior of living systems, however essential we recognize metabolism for the existence of a living system?

Those considerations and questions do not imply that metabolism, appropriately characterized, does not qualify as an essential component in the activity of living as we know it from Earth life. All Earth's orgnisms 'metabolize.' Indeed, Harold Morowitz and Eric Smith recognize a “core metabolism” in all living systems and characterize it as follows:

....we know from analysis of entire genomes (citation to: ) that the complete metabolic chart of autotrophs [organisms that synthesize their own food from inorganic materials and a source of free energy] has a universal core, based on a set of fewer than 500 small &mdash; less than 400 Dalton molecular weight–organic molecules. Within core metabolism, we recognize two major categories of function. Anabolism comprises the set of reactions that build organic compounds, while catabolism is the breaking down of organic compounds for energy or materials. Anabolism is essentially a reductive process, meaning that it consumes energy-rich electrons to create molecular bonds. It is possible for an organism to exist with anabolic reactions alone, if suitable electron donors [energy sources] are provided by its environment, and many major clades of anaerobic organisms that are thought to have very ancient lineage are autotrophs living on geochemical [energy] inputs (called chemo-autotrophs) whose metabolism is almost entirely anabolic (citation to: )

Morowitiz and Smith describe the basic reductive (electron-donating, energy-storing) anabolic network as containing the carboxylic acids of the citric acid cycle and employing them to synthesize the biochemical precursors making up the cell. Non-autotrophs (heterotrophs, which feed on other organisms) use that network of carboxylic acids in an oxidizing (electron-removing) catabolic network (the Krebs cycle) to breakdown organic compounds to C02 and to free up energy. Morowitz and Smith point out that:

....when run in the reductive direction this cycle can duplicate its own members from abiotic CO2 and electrons, a property designated network autocatalysis. Thus the reductive citric-acid cycle appears, at the level of the biosynthetic network, to be a self-contained engine of synthesis for all biochemical precursors (citation to: )

The core anabolic network, according to Morowitz and Smith, generates biological amino acids utilizing ammonia and electron donors (reducing agents, reductants), sugars, including ribose, from the citric acid cycle intermediate, pyruvate, cell membrane fatty acids from acetate, another intermediate of the cycle. More elaborate pathways leading to the complex amino acids, nucleic acids, and cofactors, follow from these elementary steps in a dense and surprisingly simple web of reactions."''

Smith and Morowitz propose:

....that rTCA [the reductive tricarboxylic acid cycle] is statistically favored among competing redox relaxation pathways under early-earth conditions and that this feature drove its emergence and also accounts for its evolutionary robustness and universality.

The core structurally-creative anabolic (energy-storing) network observed in autotrophs supplies the dynamical framework for energy to drive all living organization, as all living systems either are autotrophs or depend on the existence of autotrophs.

Evolutionary aspects of 'living'
In the human 'poetic/animistic' imagination, living systems include fires and storms. The flames of candles, forest fires, and tornadoes do qualify as non-equilibrium open systems &mdash; like the living systems of the three recognized domains of life, Archaea, Bacteria, and Eukarya &mdash; but they lack the the essential activities of living systems, all of the activities required to perpetuate the informational base they constitute. Fire can spread and split, as in large forest fires, but they eventually all die out without leaving any progeny to perpetuate their informational nature, as the trees of the forest do; forests restore their former diversity and biomass after the fire dies out. Today's forest fires carry no inherited information from the forest fires of ancient times, because those ancient fires did not possess the intrinsic self-organized mechanism for replicating and re-replicating itself, generation upon generation, an inherited mechanism, like the forest trees possess, enabling them to make copies of themselves to keep populated the forest with trees after they die out, or to re-populate it after a fire.

Fires all become fire entities spontaneously, but separately, independently, without continuity over millennial time. Tornadoes, tempests in a teapot. Fires and tornadoes haven't designed themselves to maintain continuity after their death, unlike the living things comprising the three recognized domains of life.

When a living system reproduces itself, ensuring its informational continuity, its offspring inherit its properties, but the offspring may acquire new properties and lose other ones along the course of the inheritance pathway, imperfect fidelity of informational reproduction, variations on the inherited property profile caused by random events. Some variations offer some of the offspring less opportunity to reproduce than others, and other offspring better opportunity, sometimes better even than their parents. Accordingly, new groups with different heritable property profiles arise that may supplant older groups because of greater reproductive fitness. Biologists call this evolution by "natural selection", or by "survival of the fittest", and many regard it as the most important way whereby living systems evolve over geological time.

The causes of the heritable property profile variations play a role in determining species evolution. Chance plays an influential role there. Natural experiments, like endosymbiosis, a chance event, play an important role in evolution, allowing natural selection the opportunity to select among new endosymbiotic species. Epigenetic transmission of information can introduce property profile variations that persist across generations, so might contribute to evolution by means of natural selection. Heritable properties subject to profile variations invite natural selection to act if the variations cause differences in reproductive fitness.

Evolution of living systems across reproductive generations requires variations in heritable property profiles capable of influencing reproductive fitness in circumstances where competition for reproductive fitness determines who gets to reproduce most fecundly.

Therefore, biologists recognize the ability to produce offspring that inherit some of its features, but with some variation, as an essential characteristic of living systems, one that enables descent with modification, allowing living systems to adapt to changing circumstances that determine what counts as reproductive fitness, and so perpetuation of a lineage. Evolution by natural selection will occur if heritable variations produce offspring that differ in their reproductive fitness and if circumstances induce competition among conspecifics for reproductive fecundity. The variations occur due to chance variations (e.g., mutations) in the inherited genetic database (genome) that the organism draws upon to the help it self-construct and self-maintain its organismic traits (phenotype), and also to various natural experiments (e.g., symbiogenesis) that lead to emergent genotype-phenotypes.

In all living systems, DNA primarily provides the database for the construction of their protein constituents. All living things descended with modification from an ancestral community of microorganisms with a partially shareable gene pool. (But see: To glimpse beyond that horizon, we will need to take heed of the findings of intense current research on early cellular evolution -- see Evolution of cells).

Viruses have few of these characteristics, but they do have a genotype and phenotype, making them subject to natural selection and evolution. Accordingly, descent with modification is not uniquely a characteristic of living systems. Beyond the scope of this article, we find descent with modification in memes and the artificial life of computer software, such as self-modifying computer viruses and programs created through genetic programming. Descent with modification has also been proposed to account for the evolution of the universe.

When it comes to the fundamental structures and processes of living, however, some biologists argue against the requirement for reproduction. NASA defines 'life' as a "chemical system capable of Darwinian evolution", without specification of reproduction per se (for discussion, see Benner et al. ).

Adding to the thermodynamic perspective, we might say that:

Self-organization
In living systems, the order we find results to a large degree through the ability of the system to organize itself, independently of a master controller, a program director, a blueprint, a template. Self-organization 'emerges' as a spontaneous manifestation of the interactions among the systems' components, of the system with the environment embedding it, influenced by the process of natural selection. In cells, self-organization emerges in part from so-called intermolecular or supramolecular (non-covalent) interactions of proteins-with-proteins and proteins with other molecules. The proteins make their appearance through a genetic transcription-translation machinery, which itself represents a self-organized molecular machine that emerges in part from the non-covalent interactions of proteins with nucleic acids and other molecules. Jean-Marie Lehn, of the Institut de Science et d'Ingénierie Supramoléculaires, Université Louis Pasteur, summarizes it in this way:

<font face="Comic San MS, Trebuchet MS, Consolas">A self-organization process may be considered to involve three main stages: (i) molecular recognition for the selective binding of the basic components; (ii) growth through sequential and eventually hierarchical binding of multiple components in the correct relative disposition; it may present cooperativity and nonlinear behavior; and (iii) termination of the process, requiring a built-in feature, a stop signal, that specifies the end point and signifies that the process has reached completion.

Molecules interact by forming and breaking strong or weak covalent bonds, and also through weaker intermolecular interactions, like hydrogen bonding and Van der Waals forces. Those supramolecular interactions self-assemble aggregates of molecules (e.g., organelles, networks), giving them the properties that enable many biological processes. To quote Reinhout and Crego-Calama:

<p style="margin-left:2.0%; margin-right:6%;font-size:0.95em;"><font face="Comic San MS, Trebuchet MS, Consolas">In chemistry, noncovalent interactions are now exploited for the synthesis in solution of large supramolecular aggregates. The aim of these syntheses is not only the creation of a particular structure, but also the introduction of specific chemical functions in these supramolecules..

Again, J-M Lehn:

<p style="margin-left:2.0%; margin-right:6%;font-size:0.95em;"><font face="Comic San MS, Trebuchet MS, Consolas">Starting with the investigation of the basis of molecular recognition, [supramolecular chemistry] has explored the implementation of molecular information in the programming of chemical systems towards self-organisation processes, that may occur either on the basis of design [by the chemist] or with selection of their components.

The qualifier that self-organization emerges only in part from supramolecular interactions, proteins with proteins and other molecules, reflects the involvement not only of supramolecular self-assembly but also of evolutionary mechanisms, operating on random variation through selection of molecules and networks of molecules that tend to optimize the fitness of functional self-organization — in other words, Darwinian evolution, or adaptation, operating to influence the nature of the self-organizing process.

Many workers (see: Hoelzer et al. ) emphasize self-organization as playing an explanatory role for the process of natural selection: "….it is clear that the process of SO represents a potential explanation for adaptive biological evolution." Hoelzer et al. discuss that in terms of the physics of self-organizing processes &mdash; the extraction of work through channeling free energy gradients &mdash; showing that a similar physics applies to the process of natural selection, rendering self-organization and natural selection complementary processes in sustaining living complex adaptive systems.

One must also invoke local real-time selective processes that confer stability and appropriate functionality to self-assembly, called homeostasis or adaptability. Thus, order emerges out of chaos.

Professor of Microbiology, Franklin M. Harold, offers the following definition of self-organization:

<p style="margin-left:2.0%; margin-right:6%;font-size:0.95em;"><font face="Comic San MS, Trebuchet MS, Consolas">...let me define self-organization as the emergence of supramolecular order from the interactions among numerous molecules that obey only local rules, without reference to an external template or global plan...The definition explicitly excludes order imposed by an external template, whether physical (as in a photocopier) or genetic (as in the specification of an amino acid sequence by a sequence of nucleotides)...The structure of the self-assembled complex is wholly specified by the structures of its parts and is therefore implicit in the genes that specify those parts: natural selection crafted those genes to specify parts that assemble into a functional complex.

Information resides in proteins and other molecules in virtue of their structure, and through them, information flows through cells, just as energy does, and determines their organizational nature.

One way to understand this self-organization is to view a living system as a 'computing device'. The inherited and acquired information base &mdash; the genome &mdash; specifies components which arrange themselves in accord with their physico-chemical properties &mdash; i.e., they 'compute' the system in a complex chemical reaction. Systems biologist, Denis Noble, incisively describes it:

<p style="margin-left:2.0%; margin-right:6%;font-size:0.95em;"><font face="Comic San MS, Trebuchet MS, Consolas">Genes code for protein sequences. They do not explicitly code for the interactions between proteins and other cell molecules and organelles that generate function. Nor do they indicate which proteins are on the critical path for supporting cell and organelle function in health and disease. Much of the logic of the interactions in living systems is implicit. Wherever possible, nature leaves that to the chemical properties of the molecules themselves and to the exceedingly complex way in which these properties have been exploited during evolution. It is as though the function of the genetic code, viewed as a program, is to build the components of a computer, which then self-assembles to run programs about which the genetic code knows nothing…. Yet that description under-characterizes the complexity of the system. In a multicellular organism, each cell retrieves only its own particular pieces of information from the total information base, and the selection varies with time. Each cell must perform specific computations to effect that dynamic activity. The behavior of the system's functional networks constitute those specific dynamic computations. The apparent circularity begat by adding that further characterization of the system as a 'computing device' exemplifies two-way nature of the 'computations' self-organizing the living system. With the tinkering and discovering comprising local trial-and-error and evolution’s handiwork, that 'circularity' carries out ('computes') integrative functions not explicitly encoded in the inherited and acquired information base of the system.

The molecular biologist Sidney Brenner expressed the 'computing device' metaphor this way:

<p style="margin-left:2.0%; margin-right:6%;font-size:0.95em;"><font face="Comic San MS, Trebuchet MS, Consolas">...biological systems can be viewed as special computing devices. This view emerges from considerations of how information is stored in and retrieved from the genes. Genes can only specify the properties of the proteins they code for, and any integrative properties of the system must be 'computed' by their interactions. This provides a framework for analysis by simulation and sets practical bounds on what can be achieved by reductionist models.

The structure and behavior of self-organized systems need no behind-the-scenes 'master controller', and no prepared blueprints that specify the structure and dynamics of the system. Instead, they emerge from interactions among the naturally generated and naturally selected components of a system, dictated by their physico-chemical properties, and dynamically modified by the emergent organization, which is itself modified by the environment. The single-celled zygote self-organizes into a multicellular living system as genetically encoded proteins interact, responding to changing influences from the changing environment generated by growing multicellularity &mdash; becoming a network of many cell-types working cooperatively.

That biological systems self-organize has led one prominent biologist to say they are products of a "blind watchmaker".

Self-organization tends to breed greater complexity of self-organization. One important aspect of self-organization in cells rests on the tendency for lipid molecules with polar (water-loving) and non-polar (water-shunning) ends to form bilayers in an aqueous solution, each unit of the bilayer with two lipid non-polar ends mutually attracted in the center and the polar ends surrounded by water. Protein molecules can span the bilayer membrane, or selectively straddle only one or the other side of the membrane and its aqueous surrounding, according to their specific amino-acid sequence and side-groups. Those lipid-protein membranes allow cells to communicate with other cells, either in free-living cellular communities or in multicellular organisms, and those communication activities self-organize by virtue of the properties of the cells, generated by natural experiments and selected for fitness by evolutionary mechanisms, and subject to downward effects by the systems' organization and environmental influences on the systems.

Self-organization occurs at all levels of living systems. For example, the dynamics of communities, such as the feeding relationships within communities of large mammals, also reflect self-organization. The animals and components of the ecosystem embedding them self-organize, resulting in "...unitary structures with coherent properties...[that] can operate in an integrated way, which allows for the acceptance of their changes on large time-scales as evolutionary."

Further elaborating the descriptions of living systems beyond the thermodynamic and evolutionary perspectives, we might say that:

Autonomous agents
Stuart Kauffman uses the concept of 'autonomous agents' to explain living systems. He gives the hypothetical example of an enzyme that catalyzes the binding of two smaller sub-component molecules into a copy of itself &mdash; self-replication by auto-catalysis. The energy to produce the enzyme comes from a neighboring molecule, which, by breaking an energy-rich bond, serves as a 'motor' to produce excess enzyme. The self-replication stops after using all duplicates of the motor, so external energy &mdash; perhaps from light impinging on the system &mdash; must drive the repair of the broken chemical bond, re-establishing a supply of that energy-supplying molecule, thereby re-energizing the motor. A new cycle of auto-catalytic self-replication can then begin, given an influx of external energy and 'food' (sub-components of the auto-catalytic enzyme). As an essential feature, interactions among the components of a system have effects (technically 'allosteric' effects) that help organize and coordinate its processes, allowing the self-replication to proceed.

Kauffman conceives, then, of an autocatalytic molecule in a network of molecules that has cycles of self-replication driven by external energy and materials. Such a network is a 'molecular autonomous agent' because, given external energy and ample materials, the network perpetuates its existence;. The network is autonomous because it is not controlled by outside forces even though it depends on outside energy and materials. The 'agent' is the system doing work autonomously; in this case, the work of self-replication. (That's what 'agents' do; they do work.) In this example, the agent survives by ‘eating’ outside materials and energy. Work gets done because the system remains far-from-equilibrium: as energy flows through the system, the system does its work, and in so doing dissipates the energy gradient, but it temporarily constrains the rate of dissipation by storing energy in its internal organization. The agent continues to "live" only while that far-from-equilibrium state exists, and it can be starved to 'death' by stopping the matter and energy from flowing through the system. Kauffman argues that cells, and indeed all living systems, qualify as autonomous agents, constructed from molecular autonomous agents.

Autonomous agents also interest scientists in the fields of artificial intelligence and artificial life. One careful description of autonomous agents from some members of that group adds further insight to this view of living systems:

<p style="margin-left: 2.0%; margin-right: 6%; font-size: 0.99em; font-family: Gill sans MT, Trebuchet MS;">.... An autonomous agent is a system situated within and a part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to effect what it senses in the future. It has the properties of reactivity (timely response to environmental changes; autonomy (controls its own actions); goal-orientation (pursues its own agenda); continuous processing. Some autonomous agents may also have the properties of communicability (with other agents); adaptability (based on previous experience); unscripted flexibility.

For Kauffman, the property of pursuing its own agenda includes contributing to its own survival and reproduction: "...an autonomous agent is something that can both reproduce itself and do at least one thermodynamic work cycle. It turns out that this is true of all free-living cells, excepting weird special cases. They all do work cycles, just like the bacterium spinning its flagellum as it swims up the glucose gradient. The cells in your body are busy doing work cycles all the time." There is only one escape from work, and that is death.

If the descriptions of living systems from thermodynamic, evolutionary, self-organizational and autonomous agent perspectives are considered, we might add that:

Networks
The science of networks provides another useful perspective on living things. Networks ‘re-present’ a system as 'nodes’ and ‘interactions’ among the nodes (also referred to as ‘edges’ or ‘arrows’ or ‘links’). For example, in a spoken sentence, words and phrases make up the nodes, and the interconnections of syntax (subject-to-predicate, preposition-to-object of preposition, etc.) make up the links. Intracellular molecular networks represent specific functions in the cell; molecules make up the nodes, and their interactions with other nodes make up the edges or arrows. Some networks accept inputs of one kind and return outputs of a different kind.

One finds networks everywhere in biology, from intracellular signaling pathways, to intraspecies networks, to ecosystems. Humans deliberately construct social networks of individuals working (more or less) to a common purpose, such as the U.S. Congress; they also construct networks of electronic parts to produce, for example, mobile phones; and networks of sentences and paragraphs to express messages, including this very article. Researchers view the World Wide Web as a network, and study its characteristics and dynamics.

According to Alon, "The cell can be viewed as an overlay of at least three types of networks, which describes protein-protein, protein-DNA, and protein-metabolite interactions." Alon notes that cellular networks are like many human engineered networks in that they show 'modularity', 'robustness', and 'motifs':
 * Modules comprise subnetworks with specific functions differing from those of other modules, and which typically but not invariably connect with other modules, often only at one input node and one output node. An individual module achieves its status as a distinct entity not only by its functional specificity but also by spatial specificity (e.g., ribosomes) or by chemical specificity (e.g., signal transduction networks). Modularity helps to facilitate real-time system adaptability to environmental change, as the organization of modules in the system contributes to the emergent properties of the system.  It also facilitates evolutionary adaption, as, to select an adaptation, evolution may need tinker with just a few modules rather than with the whole system. Evolution can sometimes 'exapt' existing modules for new functions that contribute to reproductive fitness. For example, Darwin surmised that the swim bladder of skeletally heavy fish evolved as an adaptation for control of buoyancy but was exapted as a respiratory organ in certain fish and in land vertebrates.
 * Robustness describes how a network is able to maintain its functionality despite environmental perturbations that affect the components. Robustness also reduces the range of network types that researchers must consider, because only certain types of networks are robust.
 * Network motifs offer economy of network design, as the same circuit can have many different uses in cellular regulation, as in the case of autoregulatory circuits and feedforward loops. Nature selects motifs in part for their ability to make networks robust, so systems use motifs that work well over and over again in many different networks. In several well-studied biological networks, the abundance of network motifs &mdash; small subnetworks &mdash; correlates with the degree of robustness. Networks, like those in cells and those in neural networks in the brain, use motifs as basic building blocks, like multicellular organisms use cells as basic building blocks. Motifs offer biologists a level of simplicity of biological functionality for their efforts to model the dynamics of organized hierarchies of networks.

The view of the cell as an overlay of mathematically-definable dynamic networks can reveal how a living system can exist as an improbable, intricate, self-orchestrated dance of molecules. The 'overlay of networks' view also suggests how the concept of self-organized networks can extend to all higher levels of living systems.

Further elaborating the descriptions of living systems beyond the thermodynamic, evolutionary, self-organizational and autonomous agent perspectives we might add that:

Information processing
Bioscientists study biological systems for many different reasons, hence biology has many subdisciplines (see Biology and List of biology topics). But in every subdiscipline, bioscientists study biological systems for the proximate reason of gaining information about the system to satisfy their however-motivated curiosity and to apply that information to human agendas (e.g., to prevent disease, to develop treatments, to enhance health and longevity, to conserve the environment, etc.). Those realities attest that biological systems harbor information, at least as people usually understand the term. Living systems not only harbor information useful to biologists, but they also acquire, generate, and employ information useful to themselves, as Lowenstein notes in the epigraph to this section. To appreciate how that perspective can contribute to understanding living systems, the following questions need answers:

&mdash;What do we mean by information? &mdash;How does information apply to biological systems? &mdash;How does information emerge in biological systems? &mdash;How do the answers to those questions add to explaining living systems?

The word 'information' comes from the verb 'to inform', originally meaning to put form into something: the seal in-forms the wax, and the wax now contains in-formation. A random collection of particles or other entities has no form, nothing has given it form, and it contains no in-formation. The more randomness in the structure of the collection, the fewer improbable arrangements or interactions it has among its parts.

A drinking glass falls onto the sidewalk, it falls apart into a random collection of bits of glass. Notice it doesn’t regroup into the drinking glass &mdash; you could watch it for a lifetime. Our experience shows us that the drinking glass is more improbable than the glass smithereens. The more improbable the arrangements, the more in-formation a collection of parts has received and therefore contains. An observer will conclude that something has happened to form the parts into a more improbable state &mdash; an in-formation has occurred, and that the collection of parts contains that in-formation. By that reasoning, biological systems contain in-formation: something has happened to 'form' the parts into an improbable state. An ordered desktop soon becomes disordered. The ordered desktop has message value, or 'information', in that something must have happened to give it form. The more unlikely the arrangement of the parts, the more information it contains. Biological systems have information content in that they are unlikely (non-random) arrangements of parts, non-random collections of interactions of parts, and non-random collections of functional activities.

The above-discussed thermodynamic and autonomous agent perspectives viewed cells as interposed between a higher-to-lower degrees of usable (free) energy &mdash; embedded in downward sloping free energy gradient. The flow of energy through the cell fuels it, enabling it to perform the work that leads it to gain form, or order, or organization, and to gain functionalities, which raises its information content.

Thus a living system emerges as an information processing system. It can receive information from energy and energy-rich materials in its environment, which fuels and supplies the self-organizing machinery that builds and sustains an information-rich organization; it can generate new information inside itself, as in embryonic development; and it can transmit information within and outside itself, as in transcription regulation and exporting pheromones. From its parent(s), it inherits information (genetic) that provides a database to help it realize its developmental potential &mdash; including information critical for its self-reproduction, though it also inherits information in non-genetic forms (epigenetic, behavioral, symbolic) that contribute to its development.

Physiologist and Director of the Laboratory of Cell Communication at the Marine Biological Laboratory, Woods Hole, Massachusetts, Werner R. Loewenstein emphasizes the reciprocal relationship between changes in information and changes in entropy: “…''we may regard the two entities as related by a simple conservation law: the sum of (macroscopic) information change and entropy change in a given system is zero. This is the law which every system in the universe…must obey.''” He elaborates:

<p style="margin-left:2.0%; margin-right:6%;font-size:1.05em; font-family:"Gill Sans MT, Trebuchet MS">Living beings continuously lose information and would sink to thermodynamic equilibrium just as surely as nonliving systems do. There is only one way to keep a system from sinking to equilibrium: to infuse new information…[T]o maintain its high order, an organism must continuously pump in information. Now, this is precisely what the protein demons do inside an organism. They take information from the environment and funnel it into the organism. By virtue of the conservation law, this means that the environment must undergo an equivalent increase in thermodynamic entropy; for every bit of information the organism gains, the entropy in the demon's environment must rise by a certain amount. There is thus a trade-off here, an information-for-entropy barter; and it is this curious trade which the protein demons ply. Indeed, they know it from the ground up and have honed it to perfection. Bartering nonstop, they draw in huge information amounts, and so manage to maintain the organism above equilibrium and locally to turn the thermodynamic arrow around.

Paul Nurse, cell biologist and president of Rockefeller University, prompts for greater focus on discovering just "how living systems gather, process store and use information" and how higher level biological phenomena emerge from such information self-management. One can envision logic circuits as proximal products of the molecular interactions occurring in a living cell, and envision ultimately the operation of selective forces in the development of those logic circuits. To understand living systems requires understanding living information processing.

Combined with other perspectives, viewing living systems as information processors, as inheritors, receivers, generators and transmitters of information, and as reproducers of inherited information, enables one to see living systems and their interactions with other living systems as a vast, complex, emergent, naturally-selected, self-sustaining, evolving communications network. Recently, on the timescale of evolving living systems, that evolving communications network emerged as the human brain, capable of communicating with itself and other humans using networks of symbols. That led to the emergence of cultural evolution, a whole new domain of self-reproducing entities ('culturgens', 'memes') and a whole new domain of descent with modification. That in turn led to the emergence of other vast communications network: books, wikis, and other technologies of information generation and exchange.

We might now consider another closely related perspective, a ‘cognitive’ perspective. Given that networks resist common perturbations (e.g., by their robustness, and by ‘homeostasis’), one might think of them as containing a representation of themselves and of their environment, and of how they might vary. As networks self-organize through interactions among proteins, any network-like 'representation’ of of the living system embedding it, and its environment, must derive from the information that determines those proteins. The genetic information comprises a molecular code, and the process that transforms that information into proteins describes an algorithm &mdash; the transcription-translation algorithm, including its regulatory circuits. Inasmuch as those algorithms evolved through natural experiment and selection, one can view evolution as selecting for cognitive functionality in the genome &mdash; the ability to ‘represent’ the cell’s state and environment and, more generally, to remember and anticipate.

Genetic information has the form of a digital code, one whose execution jump-starts self-organizing cellular processes, including the processes that lead to self-organization of networks that regulate execution of the genetic digital code &mdash; the gene regulatory networks. A separate digital code also has a central role in the operation of those gene regulatory networks: the code adjacent to a gene determines which transcription regulating factors can bind there, and thereby controls gene activity. In other words, a digital code, separate from the code that specifies the proteins of the gene regulatory networks, gives specificity to the behavior of those networks and to their regulation of the execution of the genetic digital code. Eventually, digital codes surrender to decipherment, offering the hope that we might someday read the message they contain and find ways to edit it.

Further elaborating beyond the thermodynamic, evolutionary, self-organizational, autonomous agent and network perspectives we might add that:

Living systems as self-fabricating autonomous homeostatic cognitive machines
In this section we consider living systems, as distinct from non-living systems, from the perspective of the concept of 'autopoiesis' &mdash; autonomous self-fabrication &mdash; introduced in the 1970s by Humberto Maturana (b. 1928) and Francesco Varela (1946-2001), though first enunciated, as pointed out in 2007 by J-H S. Hofmeyr, by the philosopher Immanuel Kant (1724–1804), and adumbrated by twentieth century biologists before Maturana and Varela. .

Microbiologist Harold Frank elaborates on Kant's view:

<p style="margin-left: 2.0%; margin-right: 6%; font-size: 0.99em; font-family: Gill sans MT, Trebuchet MS;">In a machine, [the German philosopher, Immanuel] Kant said, the parts exist for each other but not by each other; they work together to accomplish the machine's purpose, but their operation has nothing to do with building the machine. It is quite otherwise with organisms, whose parts not only work together but also produce the organism and all its parts. Each part is at once cause and effect, a means and an end. In consequence, while a machine implies a machine maker, an organism is a self-organizing entity. Unlike machines, which reflect their maker's intentions, organisms are “natural purposes.” Kant's vision was eminently sensible and remains true, but even he was stymied by the next stage: How can we ever discover the cause of that purposeful organization that is the hallmark of organisms?

Any entity, whether a cell or an ecosystem, that we recognize as living we recognize also as a '[[Systems biology|living system]' &mdash; Kant's 'organism' in its broadest sense &mdash; an assemblage of components, many copies of diverse types, interrelated structurally, interacting in a coordinated, dynamic, hierarchical way such as to self-construct an autonomously working organization characterizable as a ‘whole’ or ‘operational unit’ in virtue of a boundary selectively separating it from an environment — a kind of universe unto itself. We can hold that view of living systems regardless of the nature of the components that self-construct it, but on Earth we recognize those components as matter in the form of atoms and molecules, importing, converting, storing, releasing free energy, and actuated by it, all driven by physico-chemical principles, including the laws of thermodynamics.

The precise description of the organization of living things differs widely among species. Think of an ant and an anteater. We can, however, specify characteristics of the ‘kind’ of organization that all species share here on Earth. For one thing, we can say a living system’s complexity exceeds current human cognitive ability to comprehend it, even with the aid of a powerful computer exo-cortexes. Arguably, in the future that characteristic of the organization in living things may prove non-constitutive.

We can say also that the organizational state of living systems resembles that of a man-made machine, like a super-jet airplane or a super-computer, though not made by man and not obviously having a purpose except to perpetuate its activity of living. We can think of a living system as a different ‘kind’ of machine than man-made machines. We can see that living machines exhibit a natural, or non-contrived ability to keep many of its internal variables constant, or within narrow bounds, and ability to adapt to adversity and to fortunate conditions &mdash;it qualifies as both a homeostasis machine and an allostasis machine, operating autonomously.

A living system’s homeostatic and allostatic abilities play a central role in defining its uniqueness, as it enables it to homeostatically and allostatically regulate the most important variables in concert required for its continued living: an organization, whatever its description, that perpetuates its existence as a living system autonomously. Through the activity of its organization, the living system produces those components that provide the structural basis for the self-construction of its state as an autonomously self-perpetuating organization, if often through change. If a living system cannot self-maintain its organization, it cannot produce the structure whose self-constructed coordinated interactions enable it to remain a living machine.

Autopoiesis co-founder Francisco Varela summarizes thusly:

<p style="margin-left: 2.0%; margin-right: 6%; font-size: 0.99em; font-family: Gill sans MT, Trebuchet MS;">Autopoiesis attempts to define the uniqueness of the emergence that produces life in its fundamental cellular form. It's specific to the cellular level. There's a circular or network process that engenders a paradox: a self-organizing network of biochemical reactions produces molecules, which do something specific and unique: they create a boundary, a membrane, which constrains the network that has produced the constituents of the membrane. This is a logical bootstrap, a loop: a network produces entities that create a boundary, which constrains the network that produced the boundary. This bootstrap is precisely what's unique about cells. A self-distinguishing entity exists when the bootstrap is completed. This entity has produced its own boundary. It doesn't require an external agent to notice it, or to say, "I'm here." It is, by itself, a self- distinction. It bootstraps itself out of a soup of chemistry and physics.

We can view a living system then as:


 * A self-constructed machine organized as a network of interactions that fabricate, cyclically, the components whose self-organized interactions self-construct the system’s self-perpetuating network of interactions.
 * A self-constructed machine organized as a network of interactions that can respond to perturbations either by self-correction of its disturbed organization (homeostasis), or by reorganizing itself into a different self-perpetuating network of interactions (adaptability; reproduction).

We can encapsulate that view of living systems preliminarily as ‘self-constructed self-perpetuating homeostatic machines’. Maturana and Varela introduced the term ‘autopoiesis’ and ‘autopoietic organization’ to encapsulate that view of living machines as self-constructed self-perpetuating homeostatic machines as we have characterized them. Bitbol and Luisi expressed the definition of autopoiesis as follows: "The theory of autopoiesis...captures the essence of cellular life by recognizing that life is a cyclic process that produces the components that in turn self-organize in the process itself, and all within a boundary of its own making."

That view of a living system reveals a special property of homeostasis in living machines: adaptability. A human, to take an example mammal, self-perpetuates a life-sustaining organization despite enormous perturbations of its organization during embryonic and fetal ‘development’. It does it by self-reorganizing — the homeostatic property of adaptability. If we think a fetus or a child an immature adult, we must think of adults as aged fetuses or children. As one individual or identity, fetus and adult represent a single self-constructing self-perpetuating homeostatically adaptable machine.

Ontogeny highlights the living system’s unique property of homeostasis in targeting with highest priority the maintenance of an organization that produces components that self-organize a network of interactions that perpetuates that organization &mdash; including its networks of interactions that retain its homeostatic property of adaptability. Homeostatic reorganization goes on continuously. The living machine maintains networks of interactions that define it as a self-constructing self-sustaining machine.

The self-constructed self-perpetuating homeostatic machine also produces its own boundary, as without that it could not maintain its organization against all the chaos outside.

A man-made, non-living machine yields products other than itself, products for human use. A living machine yields itself as its product, a product in continuous production, no matter how much it must modify itself in the process.

Therein defines the living machine’s autonomy —- it works in its own behalf to construct and sustain itself. So central to a living machine's uniqueness, its homeostatic organizational ability to produce components whose interactions self-organize a self-perpetuating organization, that, before accumulated perturbations of its organization overwhelms its homeostatic ability, the machine self-reproduces.

By this view, neither growth nor reproduction necessarily constitute ‘primary’ abilities of living machines, as both occur, in life on Earth, as the consequence of the homeostatic adaptable activities of the self-constructing organization that fabricates components whose interactions realize that organization, along with its homeostatic adaptability. On other worlds, living systems need not necessarily grow or reproduce, so long as they can, in some way, fabricate the components that can self-organize to construct the organization that can fabricate those components, including the system’s own boundary whose character enables its individuality and access to resources and waste disposal.

Scientists can model and even synthesize experimental living machines that satisfy the basic criteria of a self-constructing self-perpetuating homeostatic machine (see ).

Access to resources alone cannot carry the day for a self-constructing homeostatic machine. It must have the ability, as part of its self-constructed organization, to recognize the resources it needs in order to sustain its organization. Recognition, however mediated, implies a type of ‘cognition’. In that case, for living machines to have an organization that produces the components that self-construct their-own component-producing organization, that organization must devote some of its activities to a type of cognition that enables it to recognize resources and import them and dispose of waste.

Those considerations dictate that a full description, or definition, of a living machine include the following:


 * An organization of components capable of producing and reproducing, cyclically, the components that self-organize to construct the organization of components that produces those components;


 * The components produced self-construct a boundary between the machine and the environment, of a nature that enables the machine to trade with the environment, acquiring the materials and/or energy required to sustain its self-perpetuating organization;


 * The components produced self-construct an organization that has the cognitive ability to recognize the resources it needs to import and the wastes it needs to export.


 * The components produced self-construct an organization that has the homeostatic ability to ‘correct’/’accommodate’ perturbations of the organization, or to reorganize appropriately to sustain a self-perpetuating organization;

With those conditions realized, we can then ask about the details of the mechanisms or conditions that effect that realization in Earth’s living machines, whose components are molecules that self-construct networks comprising an organization that recursively constructs its components of such nature that the organization they produce can operate autonomously with homeostatic adaptability to sustain or reorganize itself as a cognizing compartmented system capable of escaping thermodynamic equilibrium through repeated self-reproduction.

Further elaborating beyond the thermodynamic, evolutionary, self-organizational, autonomous agent, network and information-processing perspectives we might add that:

A living system as a hierarchy of emergent systems
(See Systems biology)

A systems perspective of 'living' recalls Aristotle's four components of causality, (see also Some modern views of the four Aristotelian causes of living) in that a living thing comprises:


 * A list of organic and inorganic parts (molecules and ions; cells, organelles, organs and organisms) &mdash; Aristotle’s 'material' cause;
 * How the parts relate to each other to form structures (e.g., networks), how they interact with each other (e.g., network dynamics), and how the structures interact with each other in a coordinated dynamic and hierarchical manner &mdash; Aristotle’s 'formal' (form-like) cause;
 * How the parts and structures became dynamically coordinated (e.g., gene expression; self-organization; competition) &mdash; Aristotle’s 'efficient' (effect-producing) cause; and
 * How the living system as-a-whole functions and behaves, and the properties that characterize it (e.g., reproduction; locomotion; cognition) &mdash; Aristotle’s 'final' cause

The analysis of all of those components together forms part of the new discipline of Systems Biology.

Systems biologists study, among other things, the phenomenon of 'emergence', whereby properties, functions and behaviors of living systems arise though not exhibited by any individual component of the system, and not explainable or predictable from complete understanding the components' properties/behaviors considered in isolation from the system that embeds them. Every cellular system exhibits emergent behaviors. Emergent behaviors of living systems include such things as locomotion, sexual display, flocking, and conscious experiencing. Even the biological components of living cells, such as mitochondria and other organelles, exhibit emergent properties.

Some biologists might find it tempting to see a type of 'vitalism', or 'life force', in living systems, given that some whole-system properties/behaviors of organisms, including even the activity of living itself, exemplify such emergent phenomena. One could not explain, for example, the action of an organism fleeing from a predator from a study of the properties of an organism's component subsystems. The properties of the component parts depend on the organization of those parts in the whole system. . Because biologists and their co-scientists can explain emergent properties/phenomena, if only sometimes in principle, by mechanisms that do not transcend interactions of matter and energy, any such ‘vitalism’ properly qualifies only as a ‘materialistic vitalism’.

One example of emergence: When components of a signaling pathway, which enable between-cell communication, interact to form the signaling system, properties can emerge &mdash; such as a self-sustaining feedback loop and generation of the signals themselves &mdash; that one cannot explain from the individuated properties of the separate components of the system.

For another example, in studying a protein separated from the system it belongs to, one can observe many of its properties, but in so studying the protein one cannot explain any of the properties it has only in the context of the system that embeds it, such as the property of catalyzing a biochemical reaction, or of binding to other proteins to form a functional protein complex. Those properties of the protein emerge in the context of the protein’s environment &mdash; how it interacts in the context of the system as a whole. Moreover, those emergent properties may result in effects within the system that, in a feedback way, further alters the properties of the protein in the system, as when a reaction product alters the catalytic properties of the protein.

Why do not all of the properties/behaviors of a system predictably result from the properties of its components? After all, the reductionist paradigm that dominated the Scientific method in the 20th century operated on the exactly opposite assumption. For one thing, the intrinsic properties of a system’s components themselves do not determine those of the whole system; rather, their 'organizational dynamics' does &mdash; how the components interact coordinately in time and space. Those organizational dynamics include not only the interrelations among the components themselves, but also interactions among the many different organizational units in the system. Secondly, the living system always operates in a certain context (its external environment, or surroundings), and those surroundings, in turn, always affect the properties of the system-as-a-whole. For example, nutrient gradients in its environment influence the direction a bacterium’s locomotion. The impact of environmental context affects the dynamic organization of the components within the system &mdash; a 'downward causation'. For another example, environmental signals can activate or suppress a metabolic pathway, reorganizing cellular activity  Note:  In relation to downward causation, the environment’s effect can sometimes reach down to the genetic database with molecular signals, altering its expression and consequently the characteristics of the cells without altering the database itself &mdash; so-called 'epigenetic' effects. When epigenetic alterations of gene expression occur in the reproductive organs, the system changes can be transmitted to the next generation. See
 * Jablonka E, Lamb MJ (2005) Evolution in Four Dimension: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge: MIT Press
 * Gorelick R (2004) Neo-Lamarckian medicine. Med Hypotheses 62:299-303 PMID 14962644.
 *  Abstract:  "Darwinian medicine is the treatment of disease based on evolution. The underlying assumption of Darwinian medicine is that traits are coded by genes, which are often assumed to be sequences of DNA nucleotides. The quantitative genetic ramification of this perspective is that traits, including disease susceptibility, are either caused by genes or by the environment, with genotype-by-environment interactions usually considered statistical artefacts. I emphasize also examining those epigenetic signals that can be altered by environmental perturbations and then transmitted to subsequent generations. Although seldom studied, environmentally-alterable meiotically-heritable epigenetic signals exist and provide a mechanism underlying genotype-by-environment interactions. Environment of a parent can affect its descendants by heritably altering epigenetic signals. Neo-Lamarckian medicine is the application of these evolutionary epigenetic notions to diseases and could have enormous public health and environmental policy implications. If industrial contaminants adversely affect organisms by meiotically-heritably altering their epigenetic signals, then cleaning up these contaminants will not remedy the problem. Once contaminants have adversely altered an individual's epigenetic signals, this harm will be transmitted to future generations even if they are not exposed to the contaminant. Exposure to environmental shocks such as free radicals or other carcinogens can alter cytosine methylation patterns on regulatory genes. This can cause cancer by up-regulating genes for cell division or by down-regulating tumour suppressor genes. Environmentally-alterable meiotically-heritable epigenetic signals could also underlie other diseases, such as diabetes, Prader-Willi syndrome, and many complex diseases. If environmentally-altered meiotically-heritable epigenetic effects are widespread - which is an important open empirical question - they have the potential to alter paradigmatic views of evolutionary medicine and the putative dichotomy of nature versus nurture. Neo-Lamarckian medicine would thereby shift emphasis from cure to prevention of diseases." One cannot simply take a living system apart and predict how it will behave in its natural environment.

As Gilbert and Sarkar puts it: “Thus, when we try to explain how the whole system behaves, we have to talk about its parts the context of the whole and cannot get away talking only about the parts.”

Philosopher of science D.M. Walsh puts it this way: "The constituent parts and processes of a living thing are related to the organism as a whole by a kind of 'reciprocal causation'." In other words, the organization of the components determine the behavior of the system, but that organization arises from more than the set of its internal components. How the whole system behaves as it interacts with its environment determines how those components organize themselves, and so novel properties of the system 'emerge' that characterize neither the environment nor that set of internal components. For example, the behavior of a human kidney cell depends not only on its cellular physiology, but also on all the properties of the organ (kidney) which constitutes its environment. The kidney's overall structure and function influence the cell’s structure and behavior (e.g., by physical confinement and by cell-to-cell signaling), which in turn influence the organization of its intracellular components. The kidney in turn responds to its environment, namely the individual body that it lives in, and that body responds to its environment, which includes such factors as the availability of particular food items, fresh water, and ambient temperature and humidity. Systems biologists regard emergent properties as arising from a combination of bottom-up and top-down effects &mdash; Walsh's 'reciprocal causation'.

Using the example of termites out of whose combined individual behaviors without outside management emerge complex colony mounds, a recent National Research Council report on the role of theory in advancing 21st century biology commented on emergent behavior as follows:

"<p style='margin-left: 2.0%; margin-right: 6%; font-size: 0.99em; font-family: Gill sans MT, Trebuchet MS;'>A reasonable way of thinking about emergent behavior might be to focus on the level or scale at which the rules reside. If the rules are specified at a low level, for example, the individual termites, and the patterns and structures, like termite mounds, emerge at a scale where there are no rules specified, we may call this emergent behavior."

Other examples of rule-free emergent behavior for which the 'rules' appear specified at a lower level than the emergent behavior itself include the flocking behavior of birds, and the folding of amino acid polymers into catalytic proteins.

Emergent processes have been recognised as, for example, contributing to understanding:


 * Subcellular morphology ,
 * Developmental biology ,
 * Metabolic networks ,
 * Proteomics
 * Evolution of complexity in living things

Emergent phenomena appear even in non-biological physical systems. Emergent phenomena attract the attention of cellular neuroscientists; and cognitive scientists. At still higher systems levels, emergent properties appear for example in the behaviour of ant colonies and the concept of swarm intelligence,  Systems scientists have simulated emergent phenomena   Emergent phenomena in human societies has also received attention. .  Biologists even explain the biosphere itself as emergent.

Emergent systems always display what we recognize as ‘complexity’, a feature we have a difficult time precisely defining. Complex systems appear to require more bits of information (words, sentences, lines of computer code, etc.) to describe than the bits of information in the system itself. The operation of the system itself supplies its own most economical model.

According the paleontologist and origin of life researcher, Robert Hazen, four basic complexity elements underpin emergence in a system:


 * A sufficiently large ‘density’ of components, with increasing complexity as the concentration increases, up to a point;


 * Sufficient interconnectivity of the components, with increasing complexity with greater and more varied types of interconnectivity, up to a point;


 * A sufficient energy flow through the system to enable the system’s components to perform the work of interacting in the self-organized way characteristic of the energized system;


 * Flow of energy through the system in a cyclic manner, presumably facilitating the spatiotemporal patterning characteristic of organized systems.

Living systems thus generate complexity and emergent properties as a hierarchy of emergent subsystems embedded in even more complex emergent systems, as in the case of an organism living in an environment of other organisms.

Further elaborating on the several perspectives described above, we may say that:

Different scientific perspectives
The different perspectives biologists use in viewing living systems can be identified as follows:


 * Living systems import free energy, energy-rich matter, order and information from their environment, and export waste in the form of degraded energy, unusable materials, and more disorder (entropy) than the order they generate within themselves. The downhill flow of free energy enables living systems to organize themselves and sustain that organization, and thus to delay (for their lifetime) the dictate of the Second Law of Thermodynamics, which states that organized systems ultimately degrade to a state of randomness;


 * The basic building blocks and working units of all living systems are cells, separated from their surroundings by a boundary membrane that allows energy, material and information exchange with their surroundings;


 * The basic (genetic) database that cells draw upon for self-organization comes as part of their starting materials. This source of information, in the form of nucleic acid macromolecules, encodes many different types of proteins that interact according to their natural physico-chemical properties to self-assemble an organization of hierarchically arranged subsystems that can import energy and export waste.


 * Cells inherit genetic and other forms of heritable information from ‘parent’ cells, raising as yet unanswered questions: how did cells arise in the first place? and how did they acquire stores of information?; (see Origin of life and Evolution of cells)


 * The molecular interactions that self-assemble and sustain the living organization are governed by the universal laws of physics and chemistry; those laws, together with the inherited information, enable a self-organizing system that can work autonomously in its own behalf for persistence of the living state and for reproduction, and allow properties and physiological functions to emerge that could not be anticipated from those of the system's components alone.


 * The activities of a living system have no 'master controller'; they need only a type of organization that maintains the system far-from-equilibrium, which can yield improbable self-organized structures and activities.


 * Living things cannot escape from real-time changes in external conditions, so they must maintain homeostasis, exhibit robustness in their organization, and must be adaptable enough to reorganize to sustain their living state. Robustness and adaptability derive from the properties of a hierarchical network of subnetworks of molecular circuits;
 * Living systems generate complexity and emergent properties as a hierarchy of emergent subsystems embedded in even more complex emergent systems, as in the case of an organism living in an environment of other organisms.


 * Living systems produce enough reproductive variability to allow evolution through natural selection, which guides the continuation of a 3.5 billion year history of Earth’s living world. By evolution, living systems generate increasing varieties of living systems, occupy an extreme spectrum of environments, create their own environments, and permit sufficient complexity to enable them to process information in a way that allows them to ‘experience’ themselves.

Synthesis of perspectives
The activity of living, for a cell-based system, depends on its ability to generate and sustain quasi-steady-states of self-organized functioning far from the state of randomness, and its ability to respond to internally and externally derived conditions that perturb its current quasi-steady-state by making adjustive responses, including self-reorganization (as in growth and development) and self-reproduction. The system attains those abilities partly and critically because of its location in the path of a downhill gradient of flowing free energy, including that stored in energy-rich molecules. It can draw off some of that downflow of energy by importing it, and it can export the inevitable wastes of degraded energy and materials it generates in performing the activities that keep it alive. It thereby generates, sustains and increases its own highly ordered and improbable state at the expense of a more than counterbalancing, more probable disordered state of its surroundings.


 * An organism lives by importing and utilizing free energy and by generating and exporting entropy.

Those principles seem to apply to all living systems: single cells, multicellular organs and organisms, and to biological systems whose parts are living systems: multi-organism demes and ecosystems. The fundamental challenges to staying alive do not differ greatly for an amoeba from those of a human. Neuroscientist Antonio Damasio puts it this way:

<p style="margin-left: 2.0%; margin-right: 6%; font-size: 0.99em; font-family: Gill sans MT, Trebuchet MS;">All living organisms from the humble amoeba to the human are born with devices designed to solve automatically, no proper reasoning required, the basic problems of life. Those problems are: finding sources of energy; incorporating and transforming energy; maintaining a chemical balance of the interior compatible with the life process; maintaining the organism's structure by repairing its wear and tear; and fending off external agents of disease and physical injury.

Professor Damasio neglected to stress the critical feature of the organism's ability to generate and export entropy &mdash; to a greater extent than it reduces its internal entropy. Without that ability, an internal entropy build-up would randomize it to premature death, though without that ability it would never have come to exist in the first place.

Steven Benner, Alonso Ricardo and Matthew Carrigan boil life down to this:

<p style="margin-left: 2.0%; margin-right: 6%; font-size: 0.99em; font-family: Gill sans MT, Trebuchet MS;">We propose that the only absolute requirements [for life] are a thermodynamic disequilibrium and temperatures consistent with chemical bonding.

With those requirements met, living things can emerge.

The building block and working unit of all living systems is the cell. For cells to utilize available external energy or energy-rich matter to achieve and maintain a state of complex organization (order), they must have, from the outset, a basic informational content, a database. That database enables the cell to self-produce components that can, by natural molecular interactions, respond to the imported energy and material to self-organize. That organization comprises modular networks of molecular interactions, and a hierarchy of interacting networks &mdash; self-organized and coordinated functional interactions. The properties of the networks and those of the hierarchy of networks enable the system to perpetuate itself, and to maintain its steady-state despite fluctuations in environmental factors. That principle, too, applies to all living systems. Any organism, plant or animal, comprises a network of organs working autonomously, maintaining its steady-state functioning far from equilibrium in response to environmental perturbations &mdash; physiologists refer to that as homeostasis, adaptability and robustness.

One can view any living organism as an autonomous cognitive living machine functioning in its own behalf, i.e., without a master controller. It comprises an organization of components capable of producing and reproducing, cyclically, the components that self-organize to construct the organization of components that produces those components. The components self-construct a boundary between the machine and the environment, of a nature that enables the machine to trade with self-interest with the environment, acquiring the materials and/or energy required to sustain its self-perpetuating organization. The components self-construct an organization that has the cognitive ability to recognize the resources it needs to import and the wastes it needs to export. The components self-construct an organization that has the homeostatic ability to ‘correct’/’accommodate’ perturbations of the organization, or to reorganize appropriately to sustain a self-perpetuating organization, including reproducing itself.

The networks that regulate the flow of information through the cell resulted from natural experiments refined and preserved by natural selection and other evolutionary processes. The databases it inherits, that evolved by natural experiment and selection, do not program living, but enable the living thing to self-produce the molecules that can interact in the very ways that contribute to self-organization of those networks that enable a cell to sustain and reproduce itself.

The collaboration of natural selection and physico-chemical laws perpetuates living systems not only in real-time but also in geological, or ‘evolutionary’, time. From common ancestors &mdash; however they may have arisen (see Evolution of cells) &mdash; informationally-guided, self-organizing, autonomous network dynamics enabled generation of the diversity of all living systems on the planet, over nearly four billion years. Living systems perpetuate living systems, exploiting free energy on its inexorable path to dissipation and degradation, and harvesting energy in developing organized systems by a more than counterbalancing dis-organizing of the larger system in which it is embedded.

Supplementary text

 * See Life/Addendum for supplementary text pertaining to this article.