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Complex systems biology (CSB) is a branch or subfield of mathematical and theoretical biology concerned with complexity of both structure and function in biological organisms, as well as the emergence and evolution of organisms and species, with emphasis being placed on the complex interactions of, and within, bionetworks,〔 〕 and on the fundamental relations and relational patterns that are essential to life.〔Donald Snooks, Graeme, "A general theory of complex living systems: Exploring the demand side of dynamics", ''Complexity'', vol. 13, no. 6, July/August 2008.〕〔Bonner, J. T. 1988. The Evolution of Complexity by Means of Natural Selection. Princeton: Princeton University Press.〕 CSB is thus a field of theoretical sciences aimed at discovering and modeling the relational patterns essential to life that has only a partial overlap with complex systems theory, and also with the systems approach to biology called systems biology; this is because the latter is restricted primarily to simplified models of biological organization and organisms, as well as to only a general consideration of philosophical or semantic questions related to complexity in biology. Moreover, a wide range of abstract theoretical complex systems are studied as a field of applied mathematics, with or without relevance to biology, chemistry or physics. ==Complexity of organisms and biosphere== A complete definition of complexity for individual organisms, species, ecosystems, biological evolution and the biosphere has eluded researchers, and still is an ongoing issue.〔〔Heylighen, Francis (2008). "Complexity and Self-Organization". In Bates, Marcia J.; Maack, Mary Niles. Encyclopedia of Library and Information Sciences. CRC. ISBN 978-0-8493-9712-7〕 Most complex system models are often formulated in terms of concepts drawn from statistical physics, information theory and non-linear dynamics; however, such approaches are not focused on, or do not include, the conceptual part of complexity related to organization and topological attributes or algebraic topology, such as network connectivity of genomes, interactomes and biological organisms that are very important.〔〔^ Heylighen, Francis (2008). "Complexity and Self-Organization". In Bates, Marcia J.; Maack, Mary Niles. Encyclopedia of Library and Information Sciences. CRC. ISBN 978-0-8493-9712-7〕〔"abstract relational biology (ARB)". PlanetPhysics. Retrieved 2010-03-17.〕 Recently, the two complementary approaches based both on information theory, network topology/abstract graph theory concepts are being combined for example in the fields of neuroscience and human cognition.〔〔http://hdl.handle.net/10101/npre.2011.6115.1 Wallace, Rodrick. When Spandrels Become Arches: Neural crosstalk and the evolution of consciousness. Available from Nature Precedings (2011)〕 It is generally agreed that there is a hierarchy of complexity levels of organization that should be considered as distinct from that of the levels of reality in ontology.〔〔http://philica.com/display_article.php?article_id=256 Baianu, I. and R. Poli. (2011). From Simple to Complex and Ultra-complex Systems: A Paradigm Shift Towards Non-Abelian Systems Dynamics. ''philo.philica.com'' Article # 256.〕 The hierarchy of complexity levels of organization in the biosphere is also recognized in modern classifications of taxonomic ranks, such as: biological domain and biosphere, biological kingdom, Phylum, biological class, order, family, genus and species. Because of their dynamic and composition variability, intrinsic "fuzziness", autopoietic attributes, ability to self-reproduce, and so on, organisms do not fit into the 'standard' definition of general systems, and they are therefore 'super-complex' in both their function and structure; organisms can be thus be defined in CSB only as 'meta-systems' of simpler dynamic systems〔〔(Metasystem Transition Theory ), Valentin Turchin, Cliff Joslyn, 1993-1997〕 Such a meta-system definition of organisms, species, 'ecosystems', and so on, is not equivalent to the definition of a ''system of systems'' as in Autopoietic Systems Theory,;〔(Reflexive Autopoietic Systems Theory )〕 it also differs from the definition proposed for example by K.D. Palmer in meta-system engineering,〔(Meta-system Engineering ), Kent D. Palmer, 1996〕 organisms being quite different from machines and automata with fixed input-output transition functions, or a continuous dynamical system with fixed phase space,〔Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System''s 14:259–270〕 contrary to the Cartesian philosophical thinking; thus, organisms cannot be defined merely in terms of a quintuple ''A'' of ''(states, startup state, input and output sets/alphabet, transition function)'',〔John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman.2000. Introduction to Automata Theory, Languages, and Computation (2nd Edition)Pearson Education. ISBN 0-201-44124-1〕 although 'non-deterministic automata', as well as 'fuzzy automata' have also been defined. Tessellation or cellular automata provide however an intuitive, visual/computational insight into the lower levels of complexity, and have therefore become an increasingly popular, discrete model studied in computability theory, applied mathematics, physics, computer science, theoretical biology/systems biology, cancer simulations and microstructure modeling. Evolving cellular automata using genetic algorithms〔The Evolutionary Design of Collective Computation in Cellular Automata, James P. Crutchfeld, Melanie Mitchell, Rajarshi Das (In J. P. Crutchfield and P. K. Schuster (editors), Evolutionary Dynamics|Exploring the Interplay of Selection, Neutrality, Accident, and Function. New York: Oxford University Press, 2002.)〕〔 Evolving Cellular Automata with Genetic Algorithms: A Review of Recent Work, Melanie Mitchell, James P. Crutchfeld, Rajarshi Das (In Proceedings of the First International Conference on Evolutionary Computation and Its Applications (EvCA'96). Moscow, Russia: Russian Academy of Sciences, 1996.)〕 is also an emerging field attempting to bridge the gap between the tessellation automata and the higher level complexity approaches in CSB. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Complex systems biology」の詳細全文を読む スポンサード リンク
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