Life/Citable Version

Biologists use the term life to refer to the processes comprising the activity of living, to the entities that embody those processes, and to the interrelations and interactions among those entities---complex adaptive systems. The question turns on what precisely characterizes the 'processes of living'. In answering that, biologists hope to find answers to many other questions in biology, perhaps even some not yet asked (see Biology and Systems biology).

This article will provide a fundamental structure enabling the reader to learn heuristically what constitutes 'living'. Until understanding emerges full-blown, the reader must, so to speak, live with the word in the contexts in which it exists during the unfolding of this article.

Linguistic Considerations Relating to the Definition of Life

Ernst Mayr, a 20th century giant among evolutionary biologists, in his last decade as a centenarian, wrote a book called This is Biology: The Science of the Living World (Mayr 1997). In his opening chapter, What Is the Meaning of “Life” [his quotation marks], he declares that understanding 'life' is one of the major objectives of biology. However, he suggests that we should fuss less about defining 'life', and concentrate more on defining the process of 'living':

Evolutionary biologist Ernst Mayr (1904-2005) in 1994. Author of: Mayr E. (2005) This is Biology: The Science of the Living World. Cambridge, Mass: Belknap Press of Harvard University Press. ISBN 067488468X. See encomium: Meyer A (2005) On the Importance of Being Ernst Mayr. PLoS Biol 3(5): e152 Click Here

"The problem here is that "life" suggests some "thing" -- a substance or force -- and for centuries philosophers and biologists have tried to identify this life substance or vital force, to no avail. In reality, the noun "life" is merely a reification of the process of living [emphasis added]. It does not exist as an independent entity. One can deal with the process of living scientifically, something one cannot do with the abstraction "life". One can describe, even attempt to define, what living is; one can define what a living organism is; and one can attempt to make a demarcation between living and nonliving. Indeed, one can even attempt to explain how living, as a process can be the product of molecules that themselves are not living." (Mayr 1997, page 2).

Scientist Eric Schneider and science writer Dorian Sagan echo Mayr:

"...the word is a grammatical misnomer: life is a noun, but the phenomenon to which it refers is a process. And it is vitalistic: when we say life, we think we know what we are talking about when often we have simply applied a label that allows us to categorize, rather than examine closely, the phenomenon about which we are speaking."

Ultimately, all definitions of words in terms of other words converge on about 70 so-called "semantic primes" (words that cannot be defined in terms of other words, which are universal among languages, and the meaning of which children learn by the way they are used in the society in which they live). Every other word can be defined using some combination of semantic primes. The verb “live” is one of these semantic primes. Using semantic primes, 'Life' is defined as 'that which lives', where lives is understood by speakers and listeners from their experience with the language-speakers in their environment; they also know primitively that things which live 'die' and generate the word 'death' to refer to 'that which died'.

The question, then, not “what is life?”, but “what characterizes things that live?” In fact, biologists act on the latter question, even as they ask it in terms of the former. The biologist, logician and historian J.H. Woodger suggested that the word "life" can be eliminated from the scientific vocabulary, because it is "an indefinable abstraction and we can get along perfectly well with "living organism" which is an entity which can be speculatively demonstrated.” Carol Cleland, philosopher and member of NASA’s Astrobiology Institute, adds that scientists are not really interested in what the word "life" happens to mean in our language. "What we really need to focus on is coming up with an adequately general theory of living systems, as opposed to a definition of "life."" Perhaps this resonates with biology professor Antonio Lazcano's remark: "Life is like music; you can describe it but not define it". ).

Differing Perspectives on What Constitutes a Living System

As well as sharing a common carbon- and water-based chemistry, entities that biologists generally acknowledge as living ——(bacteria, trees, fish, chimpanzees etc.)——share a common basic building block, the cell. The cell is the smallest system thought capable of independent living. Many organisms live as single cells, some are cooperative colonies of single cells, others are complex multicellular systems, with many different cell types specialized for different functions. Nature has produced an enormous variety of cell types in three vast ‘domains’ of living systems: Archaea, Bacteria, and Eukarya, yet all three domains share the characteristic cellular feature of compartmentalization from their environment by a surrounding lipid-protein membrane, the plasma membrane. Moreover, the cells in all three domains are ‘manufactured’ by pre-existing cells. All extract chemical energy from simple sugar molecules’ chemical bonds, converting it by chemical reactions into energy forms for many different purposes, ultimately enabling them to respond to their evolutionary imperative of self-reproduction. They all possess a molecular---(i.e., DNA)---embodied code, using esentially the same code (the ‘genetic code’) that guides the production of the many different proteins (polypeptide chains of amino acids) that give structure and function to the cells. All replicate their DNA faithfully or nearly so, and thereby have the capacity to replicate themselves.

From those basic shared characteristics, biologists view the commonalities and uniquenesses of cell types, and living systems in general, from differing perspectives, all of which contribute to understanding what constitutes 'living'.

Systems

(See main article, Systems biology).

The 'systems perspective' recalls Aristotle's four components of an explanation for a complex natural living system:

• the list of organic and inorganic parts (carbon-containing molecules and inorganic ions (Aristotle’s 'material' explanation);
• how the parts relate to each other to form substructures and how they interact with each other, and how the substructures interact interact among themselves in a coordinated dynamic, and hierarchical manner (patterns of static and dynamic form) (Aristotle’s 'formal' [form-like] explanation);
• how the parts and substructures became so organized (Aristotle’s 'efficient' [effect-producing] explanation); and,
• how the cell as-a-whole functions and behaves and the properties that characterize it (Aristotle’s 'final' explanation).

The analysis of those different components together now have formalized into an academic discipline, "Systems Biology", and they apply not just to cells but to all living systems.

Thermodynamic

Biologists sometimes view living things from the perspective of thermodynamics (thermo-, heat; -dynamics, movement)---the science of interactions among energy (capacity to do work, a driving force), heat (thermal energy), work (movement through force), and entropy (degree of disorder or of missing information). These interactions define what the thermodynamic system can and cannot do in the process of interconverting energy and work. For example, by the First Law of thermodynamics we know that when one form of energy is converted to another, there is no net loss of energy, and no net gain.

The special field of 'non-equilibrium' thermodynamics, involving the Second Law of Thermodynamics, can describe many of the characteristics of systems that remain, for a more or less long time (throughout their lifespan), in a steady-state of organized functional activity. They perform their organized functional activities far from the 'equilibrium' state of activity of the system if it did not have access to and ability to store and utilize available energy from outside the system. Such systems can store energy and perform work on themselves and outside; the available outside energy ultimately supplies the driving force that keeps the system functioning far-from-equilibrium and in disequilibrium with its environment.

Biological cells qualify as non-equilibrium thermodynamic systems because they must consume energy to live, and because they reach an equilibrium state only in death---whereupon all parts relate to each other according to spontaneous physicochemical processes. Viewing living systems from this perspective gives biologists mathematical tools to work with to learn how the system organizes itself. Those tools may help find ways to eliminate accumulated dysfunctions in the organizational activity of a living system that eventually causes it fail to maintain its optimal organization sufficently to keep the system organized and therefore far-from-equilibrium. Slowing or eliminating dysfunctions of organizational activities might increase lifespan.

We can, then, view a living system as a state of organizational activity (non-randomness) that is maintained by importing, storing and transforming energy and matter from its external environment into the work and structures required to sustain its organizational activity. In doing so, living systems produce waste and export it to the external environment, lowering the organizational state of the environment. The biological system thus maintains its internal organization at the expense of that of the external environment, leaving the environment more disorganized than the gain in organization of the living system--in keeping with the second law of thermodynamics that the total disorder (system plus environment) always increases.

Thus, the following could serves as a fundamental characterization of life, or of living systems:

• The ability to remain for a time (a "lifespan") as an organized, coordinated functioning system, in which spontaneous and external forces that tend to disturb its organization are opposed by built-in self-correcting mechanisms fueled by external resources (energy, matter) and facilitated by production and exportation of waste (disorder)---thus all the while operating far-from an ever-approaching equilibrium (the state that we call "death").

Evolutionary

The thermodynamic characterization might also apply to some non-living systems such as a tornado or the flame of a candle. However, tornados and candle flames cannot 'reproduce' themselves, as cells and organisms do. One might then characterize living systems as also having: the capability in principle of reproducing themselves before equilibrium arrives.

When a living system reproduces itself, random events (including 'mutations') introduce variations in the system's properties, functions and behavior. Some variations offer some progeny, or the progeny of some conspecific living systems, less opportunity to reproduce than others, and other progeny better opportunity, sometimes better even than their progenitors, given either changes in environmental conditions or limitations of environmental resources. Accordingly, new groups with different system properties arise, and may supplant older groups by out-competing them for resources. Biologists call that process "evolution by means of natural selection", and regard it as the most important way, though not the only one, whereby living systems evolve over historical time..

Therefore, an important characteristic of living systems is descent with modification: the ability to produce offspring that inherit some of its features, but with some variation due to chance. Evolution by means of natural selection will occur if heritable variations in the offspring result in differential reproductive fitness. The variations occur due to chance variations in the inherited genetic recipe (genotype) for constructing the offspring's phenotype. In all biological systems, DNA or the related molecule, RNA, primarily provides the genetic recipe.

Viruses have few of the characteristics of living systems described above, 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.

Enlarging the description, we can say that living systems have:

• The ability to remain (for a "lifespan") as a compartmentalized, organized, coordinated functioning system, in which spontaneous and externally forced tendencies to disorganization meet offsetting built-in self-correcting mechanisms fueled by external resources (energy, matter) and facilitated by production and exportation of waste (disorder)---thus all the while operating far-from an ever-approaching equilibrium (aka death)---and capable in principle of reproducing themselves before equilibrium arrives, and of evolving over historical time to adapt to environmental conditions.

Thus, living systems extract environmental resources and export waste (disorder) to produce functional organization with the ability to do work, reproduce with variation, and evolve transgenerationally by natural selection.

Exobiological

Exobiologists (also known as "astrobiologists") concern themselves with issues relating to the possible existence of extraterrestrial living systems. Dirk Schulze-Makuch and Louis N. Irwin, interested in guiding the recognition of extraterrestrial living systems, attempt to distill the essential characteristics of a living system. They stress these characteristics, which resonate with the systems, thermodynamic and evolutionary perspectives discussed above:

• a microenvironment with a boundary between it and its external environment,
• the capability of that microenvironment to transform energy and matter from the environment to maintain itself in a low entropy state (i.e., highly ordered or organizational state),

• therefore, the capability of that microenvironment to sustain itself in thermodynamic disequilibrium with its environment,

• the capability of that microenvironment to encode and transmit information.

Autonomous Agents

Stuart Kauffman emphasizes the concept of ‘autonomous agents’ in explaining 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---self-replication by 'auto-catalysis'. It requires energy to produce an excess of the enzyme from its subcomponents, beyond its equilibrium concentration. This comes from the release of the energy in an energy-rich bond of another molecule in the vicinity. The energy comes from breaking apart an energy-rich bond connecting that energy-rich molecule's subunits. The neighbor molecule serves as a motor to produce excess enzyme. The self-replication stops after using all duplicates of the motor, so to sustain self-replication, external energy---perhaps coming from light impinging on the system ---must drive the repair of the broken chemical bond, re-establishing an ample supply of that energy-supplying energy-rich molecule, thereby re-energizing the motor. A new cycle of 'auto-catalytic self-replication' can then begin, given an ample influx of the sub-components of the 'auto-catalytic' enzyme and of energy---food and energy.

Kauffman conceives, then, of a self-replicating autocatalytic molecule in a network of molecules that has repeat cycles of self-replication driven by external energy and materials. The network has a self-replication process as a subsystem, and a ‘motor’, namely, the breakup of an energy-rich molecule’s chemical bond, supplying energy that 'drives' the auto-catalysis self-replication, and its re-energizing repair by transduction of the outside energy source. Kauffman calls such a network a ‘molecular autonomous agent’ because, given a source of external energy (e.g., photons) and ample materials (the molecules needed to assemble the autocatalytic enzyme), the network perpetuates its existence autonomously, i.e., not controlled by outside forces even though dependent on outside energy and materials. The ‘agent’ is the system doing work autonomously, in this case the work on itself of auto-catalytic self-replication. That's what 'agents' do---they do work.

In the above case, the agent acts in its own behalf---continuing its existence by ‘eating’ outside materials and energy. Work gets done because the system remains far-from-equilibrium, with influxing excess outside energy and materials. Energy flows through the system, doing work, and the system can only do work when those far-from-equilibrium conditions persist. At equilibrium, no work gets done because no energy flows through the system. Thus the agent continues 'to live' (survive and self-replicate) only while that far-from-equilibrium state exists, and it can be starved to ‘death’ by removing the matter and energy flowing through the system.

Kauffman argues, from his example, that cells, and indeed all living systems, qualify as autonomous agents, constructed on a foundation of molecular autonomous agents.

Autonomous agents also interest scientists in the fields of artifical intelligence and artificial life. One carefully thought out description of autonomous agents from some members of that group adds further insight to Kauffman's view of living systems:

“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 acting in its own behalf as a naturally selected system contributing to its own survival and self-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.”

Networks

The science of networks provides another perspective on the nature of living things. Networks ‘re-present’ a system, or subsystem, as a collection of ‘nodes’ and ‘interactions’ among the nodes (also referred to as ‘edges’ or ‘arrows’ or ‘links’). To exemplify, 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 some kind and return outputs of a different kind.

One ‘finds’ networks everywhere in biology, from intracellular molecular networks, to intraspecies networks, to ecosystem networks: gene regulatory circuits, social groups of chimpanzees, entangled banks. Humans deliberately construct networks, of individuals working to a common purpose (e.g. the U.S Congress), of electronic parts to produce desired outputs (e.g. mobile phones), of sentences and paragraphs to express messages (e.g. this article). Researchers view the World Wide Web as a network and study its characteristics and dynamics. In reference to cells, Alon summarizes the current view: “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 resemble many types of human engineered networks, in that they exhibit what network analysts call ‘modularity’, ‘robustness’, and ‘motifs’.

• Modules comprise subnetworks that perform a specific function and that connect with other modules only at one input node and one output node. Modularity offers ease of cellular adaptation to changing environments, as, to produce the adaptation, evolution need tinker with just a single or a few modules rather than with the whole system. Evolution can exapt existing modules for novel functions that contribute to survival.
• Robustness offers continued functionality of a network in the face of typical deviations in the state of the components due to environmental perturbations. Robustness restricts the range of network types researchers have to consider because only certain types enable robustness.
• Network motifs offer economy of design, as the same circuit design can have widespread applicability in cellular regulation, as in the case of autoregulatory circuits and feedforward loops (see cell). Networks, like those in cells and those in neural networks in the brain, employ motifs as basic building blocks, like multicellular organisms employ cells as basic building blocks.

The view of the cell as an overlay of mathematically-definable dynamic networks, especially when analyzed in detail in relation to known cellular activities, can give one a revelatory experience about how a living system can exist as an improbable intricate self-orchestrated dance of molecules. It also suggests how the concept of self-organized networks can extend to all higher levels of living systems.

Self-organized networks, but not randomly self-organized. Natural selection favors self-organized networks that contribute to the reproductive fitness of the system, as they coordinate with the other self-organized networks in the system.

Information Processing

Bioscientists study biological systems for a variety of reasons. Hence biology as a discipline has many subdisciplines (e.g., microscopic anatomy, physiology, molecular biology) (see Biology and List of biology topics). But whatever the subdiscipline, bioscientists study biological systems for the proximate reason of gaining information about the system (satisfying curiosity), and for the close-by reasons of applying that information to human agendas (e.g., disease prevention, environmental conservation). Those realities attest that biological systems harbor information, at least as humans commonly view information. Examining the wealth of information about biological systems contained in an undergraduate biology textbook should dispel any doubt about that.

To appreciate how viewing biological systems from an information perspective can contribute to understanding what constitutes a living system, the following questions need answers:

• what do we mean by information?
• how does information apply to biological systems?
• how does information emerge in biological systems?
• 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 in something, to give it form. 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, 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, inasmuch as the second law of thermodynamics teaches us that the universe, and any other 'isolated' system, tends to randomness as its most probable state. 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—you could watch it for a lifetime. Our own experience (aka experiment) shows us that tThe drinking glass is more improbable than the glass in smithereens.

The more improbable the arrangements or interactions among its parts, the more in-formation a collection of parts has underwent and therefore contains. Something monitoring the collection over time has a degree of certainty that something has happened to ‘form’ the parts into a more improbable state—an in-formation has occurred, and the collection of parts contains that in-formation.

By that line of reasoning, biological systems, especially living systems, contain in-formation: something has happened to ‘form’ the parts into a more improbable state than the more probable thermodynamic state of random arrangement of parts.

Randomness, or disorder (i.e., no order or form), has a high probability of occurrence. An ordered desktop soon becomes disordered. The ordered desktop---the ordered arrangement of the parts of any collection of parts---has message value, or ‘information’, in that we know something must have happened to give it form from its more probable state of disorder. The less improbable the occurrence of disorder, the more information it harbors. The more unlikely the arrangement of the parts, the more information in the arrangement.

That becomes more intuitive in thinking about sentences. Sentences carry messages; they contain information. The more random the collection of words, the less certain the message. Consider that same collection of words randomized: “More the random certain the less the collection words of message the”. The more unlikely the collection of words, the more certain the message, the more information content.

As unlikely (non-random) arrangement of parts, as non-random collections of interactions of parts, as non-random collections of functional activities—biological systems thus have information content.

Earlier sections of perspectives on what constitutes a living system—-the thermodynamic and autonomous agent perspectives—-discussed the notion of cells—the basic building blocks of living systems—as intermediates in a gradient of higher to lower forms of usable energy, including mass-energy. The flow of energy and materials through the living system in-forms the system, energizes and feeds it, raising its information content. It also enables it to do work on itself, and that work enables it to give itself form, or order, and to give itself functionalities, further raising its information content. The cell can do work on its environment also.

Thus a living system emerges as an information processing system. It can:

• receive information from energy and materials in its environment, fueling and supplying the machinery of the cells that builds and sustains information-rich organization;
• generate new information inside itself, as in embryonic development;
• transmit information within and outside itself, as in transcription regulation and exporting pheromones.

From its parent, it inherits information establishing its developmental potential and scripting its realization, including controlling what parts of the inherited information base transmit their piece of information within or outside, depending on cell-type and environmental conditions—-and including information that enables it to reproduce its mature self.

Combined with other perspectives, viewing living systems as information banks, as inheritors of information, as generators of information, as receivers and transmitters of information, and as reproducers of inherited information—-enables one to see living systems and their interactions with other livings systems as a vast, complex, naturally-selected, self-sustaining, evolving communication network.

Recently, on the timescale of evolving living systems, that evolving network produced 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 descent with modification. Also emerging, another vast communication network: books, wikis, and other technologies of information generation and exchange.

Emergence as a Shared Characteristic of Living Systems

All cell and cellular systems exhibit properties, functions and behaviors that arise predictably from the properties of the system's components. However, they also exhibit some properties that arise from the organization of those components (see below)---but that one could not have predicted from those component properties. There are two related reasons for that constraint on prediction:

• the intrinsic properties, functions and behaviors of the system's components do not determine those of the whole system, but rather their organization within the system does, where 'organization' includes the interrelations of the components and their dynamic, coordinated, hierarchical interactions;
• the system-as-a-whole operates in its own context (its external environment) which affects the properties, functions and behaviors of the system-as-a-whole. The results of that contextual impact on the whole system in turn affect the organization of the system's components---a 'downward causation'.

In other words, the organization of the system's components determine its behavior, but that organization does not arise solely because of the intrinsic properties and behaviors of the components. The system's behavior itself influences the organization of its components. Novel behaviors of the system 'emerge' that are not predictable from knowledge of the intrinsic properties, functions and behaviors of the components alone. For example, the behavior of a kidney cell depends not only on the intrinsic characteristics of its components, but also on the organ (kidney) which constitutes its environment, because that environment influences the cell’s structure and behavior, which in turn influence the organization of the cell’s components.

Systems biologists refer to those two determinants of a system's behavior as "bottom-up" and "top-down" effects. The novel, emergent properties, functions and behaviors that result from a combination of bottom-up and top-down effects constiture another general characteristic of living systems.

Specific Characteristics Shared by All Living Things and Not Explicitly Stated Above

Living things share some very specific features not always explicitly stated above. For example,

• all living things descended from a common ancestor;
• only pre-existing cells can "manufacture" new cells;
• only pre-existing multicellular organisms can 'manufacture" new muticellular organisms;
• a membrane encloses every cell, protecting each from dissolution into its external environment;

• the cell membrane contains molecular systems that enables the cell to import usable matter and energy and to export unusable matter and energy, and others that enable it to send and receive signals to and from other cells;

• all cells have an inherited 'blueprint', or 'recipe', for constructing their components, which self-organize to carry out their naturally-selected functions;

• all cells have the capability to assemble and organize themselves from more rudimentary natal states;

• all cells and multicellular systems eventually die.

Mentionables

From the several different perspectives on what constitutes a living system, one can derive the list of features that biology textbooks often acribe to living systems:

1. Organization: A temporary organization of interrelated, coordinated, dynamically interacting hierarchy of molecular components within cells, of cellular components within organs and organisms, of organisms within species, and of species within ecosystems---each importing energy and matter, and using it to build, grow and sustain its structural organization for performing the functional activities needed to maintain that organization for reproducing itself.
2. Metabolism: Conversion of imported energy into any or all of the various forms of energy (e.g., chemical, electrical, mechanical, thermal), needed to utilize imported matter for maintaining functional organization.
3. Growth: At certain stages of its life-cycle, cells, organs, and organisms maintain a higher rate of synthesis (anabolism) than breakdown (catabolism) of structure and increase in organizational complexity. Growth occurs largely according to a "plan" for survival and reproduction. Species tend to grow in numbers of individuals as resources and other factors permit.
4. Reproduction: The ability to reproduce itself, for example, the division of one cell to form two new cells. Usually the term is applied to the production of a new individual (either asexual reproduction, from a single parent organism, or sexual reproduction from at least two differing parent organisms), although strictly speaking it also describes the production of new cells in the process of growth.
5. Gain of New Inheritable Traits.: Inheritable diversity, whether adaptive, neutral or disadvantageous, is a common feature of living things, and the starting point for natural selection. (See also:)
6. Adaptation: At the species level, the ability to gain traits through evolutionary processes that improve the members of the species chance for reproductive success; at the individual organism level, the ability to change (e.g., through learning) in ways that improve the individual's chances for reproductive success.
7. Response to stimuli: A response can take many forms, from the contraction of a unicellular organism when touched, to complex reactions involving all the senses of higher animals. A response is often expressed by motion, for example, the leaves of a plant turning toward the sun, an animal chasing its prey, or neuronal action potentials traveling down nerve fibres during thought.
8. Homeostasis: Regulation of the internal environment to maintain a near-constant state in response to perturbations; for example, sweating to cool off.

Exceptions

Not all entities that otherwise qualify as living ordinarily reproduce themselves, though they exist as reproduced living things. Biologists call such living things 'sterile'. Examples include programmed sterility (e.g., worker ants, mules); acquired sterility (due to acquired injury (disease) to the reproductive process; access sterility (lack of reproductive fitness); voluntary sterility (e.g., human couples). Obviously living things with the capacity to reproduce may die before reaching the reproductive stage in their life-cycle. Conversely, non-reproducing individuals may still effect reproduction of copies of their genes by facilitating the reproduction of kin, who share many genes (see kin selection).

Viruses would not qualify strictly as living things, but manage to 'reproduce' in living systems.

See also

• Origin of life
• Biology
• Systems biology

Appendix A

Selected Definitions of Life Offered by 19th and 20th Century Thinkers

Marcello Barbieri, Professor of Morphology and Embryology at the University of Ferrara, Italy, collected an extensive list of definitions of “Life” from scientists and philosophers of the 19th and 20th centuries. Those selected below resonate with the systems and thermodynamic perspectives of living systems:

• "The broadest and most complete definition of life will be "the continuous adjustment of internal to external relations". —Hebert Spencer (1884)

• "It is the particular manner of composition of the materials and processes, their spatial and temporal organisation which constitute what we call life." — A. Putter (1923)

• "A living organism is a system organised in a hierarchic order of many different parts, in which a great number of processes are so disposed that by means of their mutual relations, within wide limits with constant change of the materials and energies constituting the system, and also in spite of disturbances conditioned by external influences, the system ts generated or remains in the state characteristic of it, or these processes lead to the production of similar systems." — Ludwig von Bertalanffy (1933)

• "Life seems to be an orderly and lawful behaviour of matter, not based exclusively on its tendency to go from order to disorder, but based partly on existing order that is kept up." —Erwin Schrodinger (1944)

• "Life is made of three basic elements: matter, energy and information. Any element in life that is not matter and energy can be reduced to information." — P.Fong (1973)

• "A living system is an open system that is self-replicating, self-regulating, and feeds on energy from the environment." —R. Sattler (1986)

References

Published Collections of Definitions of 'Life' or 'Living Systems'

• Popa R. (2004) Chronology of Definitions and Interpretations of Life. In: Popa R, ed. Between Necessity and Probability: Searching for the Definition and Origin of Life. Berlin: Springer-Verlag 2004: pp. 197-205 Abstract & Link to Full-Text

• Quotes and source-citations from 1885 to 2002 CE

• Barbieri M. (2003) Appendix: Definitions of Life. In: The Organic Codes: An Introduction to Semantic Biology. Cambridge, UK: Cambridge University Press ISBN 0521824141

• Quotes from 1802 to 2002

Further reading not cited in text

Books and Book Chapters

• Margulis L, Sagan D. (1995) What is Life? Simon & Schuster. ISBN 0-684-81087-5
• Schrodinger E. (1944-2000) What is Life? Cambridge University Press (Canto). ISBN 0-521-42708-8 Full-Text Copy Found on Internet
• Buchanan M (2002) Nexus: Small Worlds and the Groundbreaking Science of Networks. W.W. Norton, New York. ISBN 0-393-04153-0
• Strogatz SH (2003) Sync: The Emerging Science of Spontaneous Order. Theia, New York. ISBN 0-7868-6844-9

Articles

• Hazen R. (2006) The Big Questions: What is Life? New Scientist Issue 2578, 17 November 2006, page 46-51 Full-Text
• Pace NR. (2001) Special Feature: The universal nature of biochemistry. PNAS 98:805-8 Link to Full-Text

Interviews and Commentaries

• Kauffman S. The Adjacent Possible: A Talk with Stuart Kauffman. Interview

See also

• Origin of life
• Evolution of cells
• Systems biology
• Biology

External links not cited above

• "In the Beginning..." (The Economist)

• From the preface: "How life on Earth got going is still mysterious, but not for want of ideas."

• Stanford Encyclopedia of Philosophy entry

• Excerpt from Conclusion: "“Living organisms are autopoietic systems: self-constructing, self-maintaining, energy-transducing autocatalytic entities” in which information needed to construct the next generation of organisms is stabilized in nucleic acids that replicate within the context of whole cells and work with other developmental resources during the life-cycles of organisms, but they are also “systems capable of evolving by variation and natural selection: self-reproducing entities, whose forms and functions are adapted to their environment and reflect the composition and history of an ecosystem” (Harold 2001, 232)."

• Life under extreme conditions.