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Moved page from wikipedia:en:Complex systems biology (history)
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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 [[interconnectivity|complex interactions]] of, and within, [[Biological network inference|bionetworks]],<ref>{{cite book |author1=Sprites, P |author2=Glymour, C |author3=Scheines, R |year=2000 |title= Causation, Prediction, and Search: Adaptive Computation and Machine Learning |edition=2nd |publisher=[[MIT Press]] |isbn=}}</ref> and on the fundamental relations and [[Relational algebra|relational patterns]] that are essential to life.<ref>Donald Snooks, Graeme, "A general theory of complex living systems: Exploring the demand side of dynamics", ''Complexity'', vol. 13, no. 6, July/August 2008.</ref><ref name="Bonner">Bonner, J. T. 1988. The Evolution of Complexity by Means of Natural Selection. Princeton: Princeton University Press.</ref><ref name="ReferenceA">{{cite journal | last1 = Rosen | first1 = R. | year = 1958a | title = A Relational Theory of Biological Systems | url = | journal = Bulletin of Mathematical Biophysics | volume = 20 | issue = 3| pages = 245–260 | doi=10.1007/bf02478302}}</ref><ref>{{cite journal | last1 = Baianu | first1 = I. C. | year = 2006 | title = Robert Rosen's Work and Complex Systems Biology | url = | journal = Axiomathes | volume = 16 | issue = 1–2| pages = 25–34 | doi=10.1007/s10516-005-4204-z}}</ref><ref name="Rosen">{{cite journal | last1 = Rosen | first1 = R. | year = 1958b | title = The Representation of Biological Systems from the Standpoint of the Theory of Categories | url = | journal = Bulletin of Mathematical Biophysics | volume = 20 | issue = 4| pages = 317–341 | doi=10.1007/bf02477890}}</ref> CSB is thus a field of theoretical sciences aimed at discovering and [[Relational model|modeling the relational patterns]] essential to life that has only a partial overlap with [[complex systems theory]],<ref name="springerlink">{{cite journal | last1 = Baianu | first1 = I. C. | last2 = Brown | first2 = R. | last3 = Glazebrook | first3 = J. F. | year = 2007 | title = Categorical Ontology of Complex Spacetime Structures: The Emergence of Life and Human Consciousness | url = | journal = Axiomathes | volume = 17 | issue = 3–4| pages = 223–352 | doi = 10.1007/s10516-007-9011-2 | citeseerx = 10.1.1.145.9486 }}</ref> 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.{{citation needed|date=June 2012}} 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.
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. 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.
复杂系统生物学(Complex systems biology，CSB)是数学和理论生物学的一个分支或分支，研究生物有机体的结构和功能的复杂性，以及生物体和物种的出现和进化，重点研究生物网络内部和生物网络之间的复杂相互作用，以及对生命至关重要的基本关系和关系模式。因此，CSB 是一个理论科学领域，旨在发现和建模的关系模式的基本生命，只有一部分重叠的复杂系统理论，也与生物学的系统方法称为系统生物学; 这是因为后者主要限于简化模型的生物组织和有机体，以及只有一个哲学或语义问题的复杂性在生物学的一般考虑。此外，广泛的抽象理论复杂系统作为应用数学领域的研究，与生物学，化学或物理学有关或无关。
[[File:Complex-adaptive-system.jpg|right|thumb|276px|Network Representation of a Complex Adaptive System]]
Network Representation of a Complex Adaptive System
复杂适应性系统的网络表示
==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.<ref name="Bonner" /><ref>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}}</ref>[[File:Seawifs global biosphere.jpg|thumb|right]]
A complete definition of complexity for individual organisms, species, ecosystems, biological evolution and the biosphere has eluded researchers, and still is an ongoing issue.right
对于单个生物体、物种、生态系统、生物进化和生物圈的复杂性的完整定义一直困扰着研究人员，而且仍然是一个持续的问题
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.<ref name="Rosen" /><ref>^ 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}}</ref><ref>"abstract relational biology (ARB)". PlanetPhysics. Retrieved 2010-03-17.</ref> Recently, the two complementary approaches based both on [[information theory]], [[network topology]]/[[graph theory|abstract graph theory]] concepts are being combined for example in the fields of [[neuroscience]] and [[cognition|human cognition]].<ref name="springerlink" /><ref>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)</ref> 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]].<ref name="springerlink" /><ref>{{cite journal | author = Poli R | year = 2001a | title = The Basic Problem of the Theory of Levels of Reality | url = | journal = Axiomathes | volume = 12 | issue = 3–4| pages = 261–283 | doi = 10.1023/A:1015845217681 }}</ref><ref>{{cite journal | author = Poli R | year = 1998 | title = Levels | url = | journal = Axiomathes | volume = 9 | issue = 1–2| pages = 197–211 | doi=10.1007/bf02681712| pmid = 8053082 }}</ref> The hierarchy of complexity levels of organization in the biosphere is also recognized in modern classifications
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. 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. 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. The hierarchy of complexity levels of organization in the biosphere is also recognized in modern classifications
大多数复杂系统模型通常是根据从统计物理学、信息论和非线性动力学中提取的概念来建立的; 然而，这些方法并不关注或不包括与组织和拓扑属性或代数拓扑相关的复杂性的概念部分，例如基因组的网络连接、交叉点和非常重要的生物有机体。近年来，以信息论为基础的网络拓扑/抽象图论两种互补的研究方法在神经科学和人类认知领域得到了广泛的应用。人们普遍认为，组织的复杂性层次有一个层次，应该被视为不同于本体论中的实在层次。在现代分类中，生物圈内组织的复杂程度等级也得到承认
of taxonomic ranks, such as: [[domain (biology)|biological domain]] and biosphere, [[Kingdom (biology)|biological kingdom]], [[Phylum]], [[Class (biology)|biological class]], [[Order (biology)|order]], [[Family (biology)|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-system]]s' of simpler dynamic systems<ref name="springerlink" /><ref>[http://pespmc1.vub.ac.be/MST.html Metasystem Transition Theory], [[Valentin Turchin]], [[Cliff Joslyn]], 1993-1997</ref> 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 [[Autopoiesis|Autopoietic System]]s Theory,;<ref>[http://archonic.net Reflexive Autopoietic Systems Theory]</ref> it also differs from the definition proposed for example by K.D. Palmer in meta-system engineering,<ref>[http://archonic.net/incosewg/ppframe.htm Meta-system Engineering], Kent D. Palmer, 1996</ref> organisms being quite different from machines and [[Automata theory|automata]] with fixed input-output transition functions, or a continuous [[dynamical system]] with fixed [[phase space]],<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A
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 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,; it also differs from the definition proposed for example by K.D. Palmer in meta-system engineering, organisms being quite different from machines and automata with fixed input-output transition functions, or a continuous dynamical system with fixed phase space,<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A
分类等级，如: 生物领域和生物圈，生物界，门，生物纲，目，科，属和种。由于生物体具有动态性和组成的可变性、固有的“模糊性”、自创生属性、自我繁殖能力等等，生物体不符合一般系统的“标准”定义，因此它们在功能和结构上都是“超复杂”的; 因此，在 CSB 中，生物体只能被定义为简单动态系统的“元系统”。在元系统工程中，有机体与具有固定输入输出转换函数的机器和自动机，或具有固定相空间的连续动力系统有很大的不同。变换的组合: a
Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System's'' 14:259–270</ref> 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)'',<ref>[[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}}</ref> although 'non-deterministic automata', as well as 'fuzzy automata' have also been defined. Tessellation or [[cellular automaton|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<ref>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.)</ref><ref>
Framework for Systems with Dynamic Topology. International Journal of Computing Anticipatory System's 14:259–270</ref> 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), 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<ref>
动态拓扑系统框架。国际计算期刊预期系统的14:259-270 </ref </ref > 与笛卡尔哲学思想相反; 因此，生物体不能仅仅被定义为五个 a (状态，启动状态，输入和输出集/字母表，转换函数) ，虽然“非确定性自动机” ，以及“模糊自动机”也已经被定义。镶嵌或细胞自动机提供了一个直观的，可视的/可计算的洞察力的复杂性较低的水平，因此已成为一个越来越流行的，离散模型研究在可计算性理论，应用数学，物理，计算机科学，理论生物学/系统生物学，癌症模拟和微观结构建模。使用遗传算法进化细胞自动机
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.)</ref><ref>{{cite journal | doi = 10.1073/pnas.0307811100 | last1 = Peak | first1 = West | last2 = Messinger | first2 = Mott | year = 2004 | title = Evidence for complex, collective dynamics and emergent, distributed computation in plants | journal = Proceedings of the National Academy of Sciences of the USA | volume = 101 | issue = 4| pages = 918–922 |bibcode = 2004PNAS..101..918P | pmid = 14732685 | last3 = Messinger | first3 = SM | last4 = Mott | first4 = KA | pmc = 327117}}</ref> is also an emerging field attempting to bridge the gap between the tessellation automata and the higher level complexity approaches in CSB.
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.)</ref> is also an emerging field attempting to bridge the gap between the tessellation automata and the higher level complexity approaches in CSB.
基于遗传算法的细胞自动机的演化: 最新研究回顾，Melanie Mitchell，James p. Crutchfeld，Rajarshi Das (In Proceedings of the First International Conference o n n x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x。俄罗斯，莫斯科: 俄罗斯科学院，1996年。) </ref > 也是一个新兴的领域，它试图弥合分块自动机和 CSB 中更高层次复杂性方法之间的差距。
==Topics in complex systems biology==
[[File:DNA animation.gif|thumb|right|100px|Animated Molecular Model of a DNA [[double helix]]]]
Animated Molecular Model of a DNA [[double helix]]
DNA 的动态分子模型[[双螺旋]]
[[File:Telomerase illustration.jpg|thumb|right|296px|Telomerase structure and function]]
Telomerase structure and function
端粒酶的结构与功能
[[File:MAPKpathway diagram.svg|thumb|right|140px|A Complex Signal Transduction Pathway]]
A Complex Signal Transduction Pathway
一条复杂的信号转导
The following is only a partial list of topics covered in complex systems biology:
The following is only a partial list of topics covered in complex systems biology:
以下只是复杂系统生物学所涉及的部分主题清单:
* [[Organism]]s and [[species]] relations and evolution
* [[Intertidal ecology|Interactions among Species]]
* [[Evolution]] theories and [[population genetics]]
** [[Population genetics]] models
** [[Epigenetics]]
** [[Molecular evolution]] theories
* [[Quantum computer|Quantum biocomputation]]
* [[DNA computing|Quantum genetics]]<ref>{{Cite journal | doi = 10.1007/BF02478347 | author = Rosen, R. 1960. | year = 1960| title = A quantum-theoretic approach to genetic problems | url = | journal = Bulletin of Mathematical Biophysics | volume = 22 | issue = 3| pages = 227–255 }}</ref>
* Relational biology<ref name="ReferenceA"/><ref>{{Cite journal | doi = 10.1007/s10516-005-4204-z | author = Baianu, I. C.: 2006 | year = 2006| title = Robert Rosen's Work and Complex Systems Biology | url = | journal = Axiomathes | volume = 16 | issue = 1–2| pages = 25–34 }}</ref><ref>{{Cite journal | doi = 10.1007/BF02477890 | author = Rosen, R.: 1958b | year = 1958| title = The Representation of Biological Systems from the Standpoint of the Theory of Categories | url = | journal = Bulletin of Mathematical Biophysics | volume = 20 | issue = 4| pages = 317–341 }}</ref><ref>[http://planetmath.org/?op=getobj&from=objects&id=10921 PlanetMath<!-- Bot generated title -->]</ref>
* [[DNA|Self-reproduction]]<ref>{{cite web|url=http://planetmath.org/?method=l2h&from=objects&name=NaturalTransformationsOfOrganismicStructures&op=getobj|title=PlanetMath |publisher=PlanetMath |date= |accessdate=2010-03-17}}</ref> (also called [[self-replication]] in a more general context)
* [[Computational gene|Computational gene models]]
** [[DNA topology]]
** [[DNA sequencing theory]]
*[[Evolutionary developmental biology]]
* [[Autopoiesis]]
* [[Protein folding]]
* [[Telomerase]] conformations and functions ''in vivo''
* [[Epigenetics]]
* [[Interactomics]]<ref name="Faith2007">
{{cite journal
{{cite journal
{引用期刊
| author = Faith, JJ
| author = Faith, JJ
作者 = Faith，JJ
| year = 2007
| year = 2007
2007年
| title = Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles
| title = Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles
| title = 大比例绘制和验证表达式概要中的大肠桿菌转录调控
| journal = [[PLOS Biology]]
| journal = PLOS Biology
| journal = PLOS Biology
| volume = 5 | issue = 1 | pages = 54–66
| volume = 5 | issue = 1 | pages = 54–66
5 | issue = 1 | pages = 54-66
| doi = 10.1371/journal.pbio.0050008
| doi = 10.1371/journal.pbio.0050008
10.1371/journal.pbio. 0050008
| pmid = 17214507
| pmid = 17214507
17214507
| pmc = 1764438
| pmc = 1764438
1764438
| display-authors = 1
| display-authors = 1
| display-authors = 1
| last2 = Hayete
| last2 = Hayete
2 = Hayete
| first2 = Boris
| first2 = Boris
2 = Boris
| last3 = Thaden
| last3 = Thaden
3 = Thaden
| first3 = Joshua T.
| first3 = Joshua T.
3 = Joshua t.
| last4 = Mogno
| last4 = Mogno
4 = Mogno
| first4 = Ilaria
| first4 = Ilaria
4 = Ilaria
| last5 = Wierzbowski
| last5 = Wierzbowski
5 = Wierzbowski
| first5 = Jamey
| first5 = Jamey
5 = Jamey
| last6 = Cottarel
| last6 = Cottarel
6 = Cottarel
| first6 = Guillaume
| first6 = Guillaume
6 = Guillaume
| last7 = Kasif
| last7 = Kasif
7 = Kasif
| first7 = Simon
| first7 = Simon
7 = Simon
| last8 = Collins
| last8 = Collins
8 = Collins
| first8 = James J.
| first8 = James J.
8 = James j.
| last9 = Gardner
| last9 = Gardner
9 = Gardner
| first9 = Timothy S.
| first9 = Timothy S.
9 = Timothy s.
}}</ref><ref name="Hayete2007">
}}</ref><ref name="Hayete2007">
} </ref > < ref name ="hayete2007">
{{cite journal
{{cite journal
{引用期刊
|author1=Hayete, B |author2=Gardner, TS |author3=Collins, JJ | year = 2007
|author1=Hayete, B |author2=Gardner, TS |author3=Collins, JJ | year = 2007
1 = Hayete，b | author2 = Gardner，TS | author3 = Collins，JJ | year = 2007
| title = Size matters: network inference tackles the genome scale
| title = Size matters: network inference tackles the genome scale
| title = 规模问题: 网络推理解决了基因组规模
| journal = [[Molecular Systems Biology]]
| journal = Molecular Systems Biology
分子系统生物学
| volume = 3 |issue = 1| pages = 77
| volume = 3 |issue = 1| pages = 77
3 | issue = 1 | pages = 77
| doi = 10.1038/msb4100118
| doi = 10.1038/msb4100118
| doi = 10.1038/msb4100118
| pmid = 17299414
| pmid = 17299414
17299414
| pmc = 1828748
| pmc = 1828748
1828748
}}</ref>
}}</ref>
} </ref >
* [[Cell signaling]]
* [[Signal transduction|Signal transduction networks]]
* [[neural net|Complex neural nets]]
* [[Gene network|Genetic networks]]
* [[Morphogenesis]]
* [[Digital morphogenesis]]
* [[Complex adaptive system]]s
* [[Catastrophe theory|Topological models of morphogenesis]]
* [[Population dynamics of fisheries]]
* [[Epidemiology]]
* [[Theoretical ecology]]
* Immune system
==See also==
{{Portal|Systems science|Mathematics}}
{{Biological classification}}
{{colbegin}}
*[[Mathematical and theoretical biology]]
*[[Abstract relational biology]]
* [[Complexity]]
*[[Complex system]]
*[[Biological system]]
* [[Systems theory]]
* [[Dynamical system]]
* [[Dynamical systems theory]]
* [[Automata theory]]
* [[Cellular automaton]]
*[[Systems biology]]
* [[Systems theory in anthropology]]
* [[Self-organization]]
* [[Nonlinearity]]
* [[Generative sciences]]
* [[Emergence]]
* [[Biosphere]]
*[[DNA]]
* [[Quantum biology]]
** [[Quantum mechanics|Quantum genetics]]
** [[Quantum chemistry|Quantum biochemistry]]
** [[Quantum chemistry]]
** [[Molecular dynamics|Quantum molecular dynamics]]
*[[Protein folding]]
*[[Interactomics]]<ref name="Faith2007" /><ref name="Hayete2007" />
*[[Genomics]]
*[[Proteomics]]
*[[Epigenetics]]
* [[Digital morphogenesis]]
* [[Complex adaptive system]]
* [[Multi-agent system]]s
* [[Cognitive Science]]
* [[Pattern oriented modeling]]
* [[Volatility, uncertainty, complexity and ambiguity]]
* [[blue Gene]]
* [[Folding@home]]
* [[Telomerase]]
* [[What Is Life?]]
{{colend}}
==Biographies==
{{colbegin}}
* [[Charles Darwin]]
* [[D'Arcy Thompson]]
* [[William Ross Ashby]]
* [[Ludwig von Bertalanffy]]
* [[Ronald Brown (mathematician)|Ronald Brown]]
* [[Joseph Fourier]]
* [[Brian Goodwin]]
* [[George Karreman]]
* [[Charles S. Peskin]]
* [[Nicolas Rashevsky]]
* [[Robert Rosen (theoretical biologist)|Robert Rosen]]
* [[Anatol Rapoport]]
* [[Rosalind Franklin]]
* [[Francis Crick]]
* [[René Thom]]
* [[Vito Volterra]]
* [[Norbert Wiener]]
{{colend}}
==Notes==
{{Reflist|colwidth=30em}}
===References cited===
* {{cite journal | last1 = Ahmed | first1 = E. | year = 2006 | title = On modeling the immune system as a complex system | url = | journal = Theor. BioSci. | volume = 124 | issue = 3–4| pages = 413–8 | bibcode = 2008arXiv0801.0847A | arxiv = 0801.0847 | doi = 10.1016/j.thbio.2005.07.001 | pmid = 17046369 }}
* Baianu, I. C., Computer Models and Automata Theory in Biology and Medicine., ''Monograph'', Ch.11 in M. Witten (Editor), ''Mathematical Models in Medicine'', vol. 7., Vol. 7: 1513-1577 (1987),Pergamon Press:New York, (updated by Hsiao Chen Lin in 2004 {{ISBN|0-08-036377-6}}
* Bonner, J. T. 1988. ''The Evolution of Complexity by Means of Natural Selection''. Princeton: Princeton University Press.
* Donald Snooks, Graeme, "A general theory of complex living systems: Exploring the demand side of dynamics", ''Complexity'', vol. 13, no. 6, July/August 2008.
* Drazin, P.G., ''Nonlinear systems''. [[Cambridge University Press|C.U.P.]], 1992. {{ISBN|0-521-40668-4}}
* Edelstein-Keshet, L., ''Mathematical Models in Biology''. SIAM, 2004. {{ISBN|0-07-554950-6}}
* Forgacs, G.; S. A. Newman, ''Biological Physics of the Developing Embryo''. C.U.P., 2005. {{ISBN|0-521-78337-2}}
* {{cite journal |author=Israel G |title=On the contribution of Volterra and Lotka to the development of modern biomathematics |journal=History and Philosophy of the Life Sciences |volume=10 |issue=1 |pages=37–49 |year=1988 |pmid=3045853}}
* Israel, G., 2005, "Book on mathematical biology" in [[Ivor Grattan-Guinness|Grattan-Guinness, I.]], ed., ''Landmark Writings in Western Mathematics''. Elsevier: 936-44.
* Jordan, D.W.; Smith, P., ''Nonlinear ordinary differential equations'', 2nd ed. O.U.P., 1987. {{ISBN|0-19-856562-3}}
* Kampen, N.G. van. ''Stochastic Processes in Physics and Chemistry'', North Holland., 3rd ed. 2001, {{ISBN|0-444-89349-0}}
* Murray, J.D., ''Mathematical Biology''. Springer-Verlag, 3rd ed. in 2 vols.: ''Mathematical Biology: I. An Introduction'', 2002 {{ISBN|0-387-95223-3}}; ''Mathematical Biology: II. Spatial Models and Biomedical Applications'', 2003 {{ISBN|0-387-95228-4}}.
* Nicolas Rashevsky. (1938)., ''Mathematical Biophysics''. Chicago: University of Chicago Press.
* Preziosi, L., ''Cancer Modelling and Simulation''. Chapman Hall/CRC Press, 2003. {{ISBN|1-58488-361-8}}.
* Renshaw, E., ''Modelling biological populations in space and time''. C.U.P., 1991. {{ISBN|0-521-44855-7}}
* Rosen, Robert.1991, ''Life Itself: A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life'', Columbia University Press, published posthumously:
* Rosen, Robert .1970. ''Dynamical system theory in biology''. New York, Wiley-Interscience. {{ISBN|0-471-73550-7}}
* Rosen, Robert. 2000, ''Essays on Life Itself'', Columbia University Press.
* Rosen, Robert. 2003, "''Anticipatory Systems; Philosophical, Mathematical, and Methodolical Foundations''", Rosen Enterprises publs.
* Rubinow, S.I., ''Introduction to mathematical biology''. John Wiley, 1975. {{ISBN|0-471-74446-8}}
* {{cite journal |author=Scudo FM |title=Vito Volterra and theoretical ecology |journal=Theoretical Population Biology |volume=2 |issue=1 |pages=1–23 |date=March 1971 |pmid=4950157 |doi=10.1016/0040-5809(71)90002-5}}
* Segel, L.A., ''Modeling dynamic phenomena in molecular and cellular biology''. C.U.P., 1984. {{ISBN|0-521-27477-X}}.
* Strogatz, S.H., ''Nonlinear dynamics and Chaos: Applications to Physics, Biology, Chemistry, and Engineering.'' Perseus, 2001, {{ISBN|0-7382-0453-6}}
* Thompson, D'Arcy W., 1992. ''On Growth and Form''. Dover reprint of 1942, 2nd ed. (1st ed., 1917). {{ISBN|0-486-67135-6}}
==Further reading==
*[https://web.archive.org/web/20160119231346/http://www.kli.ac.at/theorylab/index.html A general list of Theoretical biology/Mathematical biology references, including an updated list of actively contributing authors].
*[http://planetmath.org/?method=l2h&from=objects&id=10746&op=getobj A list of references for applications of category theory in relational biology].
*[http://www.people.vcu.edu/~mikuleck/rosen.htm An updated list of publications of theoretical biologist Robert Rosen]
* [http://homepage.uibk.ac.at/~c720126/humanethologie/ws/medicus/block1/inhalt.html Theory of Biological Anthropology (Documents No. 9 and 10 in English)]
* [http://www.scientistsolutions.com/t5844-Drawing+the+line+between+Theoretical+and+Basic+Biology.html Drawing the Line Between Theoretical and Basic Biology], a forum article by Isidro A. T. Savillo
* {{cite journal|title=Synthesis and Analysis of a Biological System|journal=Genome Informatics Series|number=Sers 10|pages=352–353|oclc=203735966|year=1999|last1=Kurata|first1=Hiroyuki|last2=Taira|first2=K|last3=Kitano|first3=H}}
{{Systems}}
[[Category:Mathematical and theoretical biology]]
Category:Mathematical and theoretical biology
类别: 数学和理论生物学
[[Category:Bioinformatics]]
Category:Bioinformatics
类别: 生物信息学
[[Category:Epidemiology]]
Category:Epidemiology
类别: 流行病学
[[Category:Biostatistics]]
Category:Biostatistics
类别: 生物统计学
[[Category:Biotechnology]]
Category:Biotechnology
类别: 生物技术
[[Category:Complex systems theory]]
Category:Complex systems theory
范畴: 复杂系统理论
[[Category:Systems science]]
Category:Systems science
类别: 系统科学
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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 [[interconnectivity|complex interactions]] of, and within, [[Biological network inference|bionetworks]],<ref>{{cite book |author1=Sprites, P |author2=Glymour, C |author3=Scheines, R |year=2000 |title= Causation, Prediction, and Search: Adaptive Computation and Machine Learning |edition=2nd |publisher=[[MIT Press]] |isbn=}}</ref> and on the fundamental relations and [[Relational algebra|relational patterns]] that are essential to life.<ref>Donald Snooks, Graeme, "A general theory of complex living systems: Exploring the demand side of dynamics", ''Complexity'', vol. 13, no. 6, July/August 2008.</ref><ref name="Bonner">Bonner, J. T. 1988. The Evolution of Complexity by Means of Natural Selection. Princeton: Princeton University Press.</ref><ref name="ReferenceA">{{cite journal | last1 = Rosen | first1 = R. | year = 1958a | title = A Relational Theory of Biological Systems | url = | journal = Bulletin of Mathematical Biophysics | volume = 20 | issue = 3| pages = 245–260 | doi=10.1007/bf02478302}}</ref><ref>{{cite journal | last1 = Baianu | first1 = I. C. | year = 2006 | title = Robert Rosen's Work and Complex Systems Biology | url = | journal = Axiomathes | volume = 16 | issue = 1–2| pages = 25–34 | doi=10.1007/s10516-005-4204-z}}</ref><ref name="Rosen">{{cite journal | last1 = Rosen | first1 = R. | year = 1958b | title = The Representation of Biological Systems from the Standpoint of the Theory of Categories | url = | journal = Bulletin of Mathematical Biophysics | volume = 20 | issue = 4| pages = 317–341 | doi=10.1007/bf02477890}}</ref> CSB is thus a field of theoretical sciences aimed at discovering and [[Relational model|modeling the relational patterns]] essential to life that has only a partial overlap with [[complex systems theory]],<ref name="springerlink">{{cite journal | last1 = Baianu | first1 = I. C. | last2 = Brown | first2 = R. | last3 = Glazebrook | first3 = J. F. | year = 2007 | title = Categorical Ontology of Complex Spacetime Structures: The Emergence of Life and Human Consciousness | url = | journal = Axiomathes | volume = 17 | issue = 3–4| pages = 223–352 | doi = 10.1007/s10516-007-9011-2 | citeseerx = 10.1.1.145.9486 }}</ref> 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.{{citation needed|date=June 2012}} 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.
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. 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.
复杂系统生物学(Complex systems biology，CSB)是数学和理论生物学的一个分支或分支，研究生物有机体的结构和功能的复杂性，以及生物体和物种的出现和进化，重点研究生物网络内部和生物网络之间的复杂相互作用，以及对生命至关重要的基本关系和关系模式。因此，CSB 是一个理论科学领域，旨在发现和建模的关系模式的基本生命，只有一部分重叠的复杂系统理论，也与生物学的系统方法称为系统生物学; 这是因为后者主要限于简化模型的生物组织和有机体，以及只有一个哲学或语义问题的复杂性在生物学的一般考虑。此外，广泛的抽象理论复杂系统作为应用数学领域的研究，与生物学，化学或物理学有关或无关。
[[File:Complex-adaptive-system.jpg|right|thumb|276px|Network Representation of a Complex Adaptive System]]
Network Representation of a Complex Adaptive System
复杂适应性系统的网络表示
==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.<ref name="Bonner" /><ref>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}}</ref>[[File:Seawifs global biosphere.jpg|thumb|right]]
A complete definition of complexity for individual organisms, species, ecosystems, biological evolution and the biosphere has eluded researchers, and still is an ongoing issue.right
对于单个生物体、物种、生态系统、生物进化和生物圈的复杂性的完整定义一直困扰着研究人员，而且仍然是一个持续的问题
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.<ref name="Rosen" /><ref>^ 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}}</ref><ref>"abstract relational biology (ARB)". PlanetPhysics. Retrieved 2010-03-17.</ref> Recently, the two complementary approaches based both on [[information theory]], [[network topology]]/[[graph theory|abstract graph theory]] concepts are being combined for example in the fields of [[neuroscience]] and [[cognition|human cognition]].<ref name="springerlink" /><ref>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)</ref> 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]].<ref name="springerlink" /><ref>{{cite journal | author = Poli R | year = 2001a | title = The Basic Problem of the Theory of Levels of Reality | url = | journal = Axiomathes | volume = 12 | issue = 3–4| pages = 261–283 | doi = 10.1023/A:1015845217681 }}</ref><ref>{{cite journal | author = Poli R | year = 1998 | title = Levels | url = | journal = Axiomathes | volume = 9 | issue = 1–2| pages = 197–211 | doi=10.1007/bf02681712| pmid = 8053082 }}</ref> The hierarchy of complexity levels of organization in the biosphere is also recognized in modern classifications
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. 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. 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. The hierarchy of complexity levels of organization in the biosphere is also recognized in modern classifications
大多数复杂系统模型通常是根据从统计物理学、信息论和非线性动力学中提取的概念来建立的; 然而，这些方法并不关注或不包括与组织和拓扑属性或代数拓扑相关的复杂性的概念部分，例如基因组的网络连接、交叉点和非常重要的生物有机体。近年来，以信息论为基础的网络拓扑/抽象图论两种互补的研究方法在神经科学和人类认知领域得到了广泛的应用。人们普遍认为，组织的复杂性层次有一个层次，应该被视为不同于本体论中的实在层次。在现代分类中，生物圈内组织的复杂程度等级也得到承认
of taxonomic ranks, such as: [[domain (biology)|biological domain]] and biosphere, [[Kingdom (biology)|biological kingdom]], [[Phylum]], [[Class (biology)|biological class]], [[Order (biology)|order]], [[Family (biology)|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-system]]s' of simpler dynamic systems<ref name="springerlink" /><ref>[http://pespmc1.vub.ac.be/MST.html Metasystem Transition Theory], [[Valentin Turchin]], [[Cliff Joslyn]], 1993-1997</ref> 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 [[Autopoiesis|Autopoietic System]]s Theory,;<ref>[http://archonic.net Reflexive Autopoietic Systems Theory]</ref> it also differs from the definition proposed for example by K.D. Palmer in meta-system engineering,<ref>[http://archonic.net/incosewg/ppframe.htm Meta-system Engineering], Kent D. Palmer, 1996</ref> organisms being quite different from machines and [[Automata theory|automata]] with fixed input-output transition functions, or a continuous [[dynamical system]] with fixed [[phase space]],<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A
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 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,; it also differs from the definition proposed for example by K.D. Palmer in meta-system engineering, organisms being quite different from machines and automata with fixed input-output transition functions, or a continuous dynamical system with fixed phase space,<ref>Hoff, M.A., Roggia, K.G., Menezes, P.B.:(2004). Composition of Transformations: A
分类等级，如: 生物领域和生物圈，生物界，门，生物纲，目，科，属和种。由于生物体具有动态性和组成的可变性、固有的“模糊性”、自创生属性、自我繁殖能力等等，生物体不符合一般系统的“标准”定义，因此它们在功能和结构上都是“超复杂”的; 因此，在 CSB 中，生物体只能被定义为简单动态系统的“元系统”。在元系统工程中，有机体与具有固定输入输出转换函数的机器和自动机，或具有固定相空间的连续动力系统有很大的不同。变换的组合: a
Framework for Systems with Dynamic Topology. ''International Journal of Computing Anticipatory System's'' 14:259–270</ref> 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)'',<ref>[[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}}</ref> although 'non-deterministic automata', as well as 'fuzzy automata' have also been defined. Tessellation or [[cellular automaton|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<ref>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.)</ref><ref>
Framework for Systems with Dynamic Topology. International Journal of Computing Anticipatory System's 14:259–270</ref> 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), 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<ref>
动态拓扑系统框架。国际计算期刊预期系统的14:259-270 </ref </ref > 与笛卡尔哲学思想相反; 因此，生物体不能仅仅被定义为五个 a (状态，启动状态，输入和输出集/字母表，转换函数) ，虽然“非确定性自动机” ，以及“模糊自动机”也已经被定义。镶嵌或细胞自动机提供了一个直观的，可视的/可计算的洞察力的复杂性较低的水平，因此已成为一个越来越流行的，离散模型研究在可计算性理论，应用数学，物理，计算机科学，理论生物学/系统生物学，癌症模拟和微观结构建模。使用遗传算法进化细胞自动机
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.)</ref><ref>{{cite journal | doi = 10.1073/pnas.0307811100 | last1 = Peak | first1 = West | last2 = Messinger | first2 = Mott | year = 2004 | title = Evidence for complex, collective dynamics and emergent, distributed computation in plants | journal = Proceedings of the National Academy of Sciences of the USA | volume = 101 | issue = 4| pages = 918–922 |bibcode = 2004PNAS..101..918P | pmid = 14732685 | last3 = Messinger | first3 = SM | last4 = Mott | first4 = KA | pmc = 327117}}</ref> is also an emerging field attempting to bridge the gap between the tessellation automata and the higher level complexity approaches in CSB.
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.)</ref> is also an emerging field attempting to bridge the gap between the tessellation automata and the higher level complexity approaches in CSB.
基于遗传算法的细胞自动机的演化: 最新研究回顾，Melanie Mitchell，James p. Crutchfeld，Rajarshi Das (In Proceedings of the First International Conference o n n x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x。俄罗斯，莫斯科: 俄罗斯科学院，1996年。) </ref > 也是一个新兴的领域，它试图弥合分块自动机和 CSB 中更高层次复杂性方法之间的差距。
==Topics in complex systems biology==
[[File:DNA animation.gif|thumb|right|100px|Animated Molecular Model of a DNA [[double helix]]]]
Animated Molecular Model of a DNA [[double helix]]
DNA 的动态分子模型[[双螺旋]]
[[File:Telomerase illustration.jpg|thumb|right|296px|Telomerase structure and function]]
Telomerase structure and function
端粒酶的结构与功能
[[File:MAPKpathway diagram.svg|thumb|right|140px|A Complex Signal Transduction Pathway]]
A Complex Signal Transduction Pathway
一条复杂的信号转导
The following is only a partial list of topics covered in complex systems biology:
The following is only a partial list of topics covered in complex systems biology:
以下只是复杂系统生物学所涉及的部分主题清单:
* [[Organism]]s and [[species]] relations and evolution
* [[Intertidal ecology|Interactions among Species]]
* [[Evolution]] theories and [[population genetics]]
** [[Population genetics]] models
** [[Epigenetics]]
** [[Molecular evolution]] theories
* [[Quantum computer|Quantum biocomputation]]
* [[DNA computing|Quantum genetics]]<ref>{{Cite journal | doi = 10.1007/BF02478347 | author = Rosen, R. 1960. | year = 1960| title = A quantum-theoretic approach to genetic problems | url = | journal = Bulletin of Mathematical Biophysics | volume = 22 | issue = 3| pages = 227–255 }}</ref>
* Relational biology<ref name="ReferenceA"/><ref>{{Cite journal | doi = 10.1007/s10516-005-4204-z | author = Baianu, I. C.: 2006 | year = 2006| title = Robert Rosen's Work and Complex Systems Biology | url = | journal = Axiomathes | volume = 16 | issue = 1–2| pages = 25–34 }}</ref><ref>{{Cite journal | doi = 10.1007/BF02477890 | author = Rosen, R.: 1958b | year = 1958| title = The Representation of Biological Systems from the Standpoint of the Theory of Categories | url = | journal = Bulletin of Mathematical Biophysics | volume = 20 | issue = 4| pages = 317–341 }}</ref><ref>[http://planetmath.org/?op=getobj&from=objects&id=10921 PlanetMath<!-- Bot generated title -->]</ref>
* [[DNA|Self-reproduction]]<ref>{{cite web|url=http://planetmath.org/?method=l2h&from=objects&name=NaturalTransformationsOfOrganismicStructures&op=getobj|title=PlanetMath |publisher=PlanetMath |date= |accessdate=2010-03-17}}</ref> (also called [[self-replication]] in a more general context)
* [[Computational gene|Computational gene models]]
** [[DNA topology]]
** [[DNA sequencing theory]]
*[[Evolutionary developmental biology]]
* [[Autopoiesis]]
* [[Protein folding]]
* [[Telomerase]] conformations and functions ''in vivo''
* [[Epigenetics]]
* [[Interactomics]]<ref name="Faith2007">
{{cite journal
{{cite journal
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| author = Faith, JJ
作者 = Faith，JJ
| year = 2007
| year = 2007
2007年
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| title = 大比例绘制和验证表达式概要中的大肠桿菌转录调控
| journal = [[PLOS Biology]]
| journal = PLOS Biology
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| volume = 5 | issue = 1 | pages = 54–66
5 | issue = 1 | pages = 54-66
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| doi = 10.1371/journal.pbio.0050008
10.1371/journal.pbio. 0050008
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17214507
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1764438
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| last3 = Thaden
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| last6 = Cottarel
6 = Cottarel
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| last7 = Kasif
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| last8 = Collins
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8 = James j.
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| first9 = Timothy S.
| first9 = Timothy S.
9 = Timothy s.
}}</ref><ref name="Hayete2007">
}}</ref><ref name="Hayete2007">
} </ref > < ref name ="hayete2007">
{{cite journal
{{cite journal
{引用期刊
|author1=Hayete, B |author2=Gardner, TS |author3=Collins, JJ | year = 2007
|author1=Hayete, B |author2=Gardner, TS |author3=Collins, JJ | year = 2007
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| title = Size matters: network inference tackles the genome scale
| title = Size matters: network inference tackles the genome scale
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| journal = [[Molecular Systems Biology]]
| journal = Molecular Systems Biology
分子系统生物学
| volume = 3 |issue = 1| pages = 77
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3 | issue = 1 | pages = 77
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| doi = 10.1038/msb4100118
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| pmid = 17299414
| pmid = 17299414
17299414
| pmc = 1828748
| pmc = 1828748
1828748
}}</ref>
}}</ref>
} </ref >
* [[Cell signaling]]
* [[Signal transduction|Signal transduction networks]]
* [[neural net|Complex neural nets]]
* [[Gene network|Genetic networks]]
* [[Morphogenesis]]
* [[Digital morphogenesis]]
* [[Complex adaptive system]]s
* [[Catastrophe theory|Topological models of morphogenesis]]
* [[Population dynamics of fisheries]]
* [[Epidemiology]]
* [[Theoretical ecology]]
* Immune system
==See also==
{{Portal|Systems science|Mathematics}}
{{Biological classification}}
{{colbegin}}
*[[Mathematical and theoretical biology]]
*[[Abstract relational biology]]
* [[Complexity]]
*[[Complex system]]
*[[Biological system]]
* [[Systems theory]]
* [[Dynamical system]]
* [[Dynamical systems theory]]
* [[Automata theory]]
* [[Cellular automaton]]
*[[Systems biology]]
* [[Systems theory in anthropology]]
* [[Self-organization]]
* [[Nonlinearity]]
* [[Generative sciences]]
* [[Emergence]]
* [[Biosphere]]
*[[DNA]]
* [[Quantum biology]]
** [[Quantum mechanics|Quantum genetics]]
** [[Quantum chemistry|Quantum biochemistry]]
** [[Quantum chemistry]]
** [[Molecular dynamics|Quantum molecular dynamics]]
*[[Protein folding]]
*[[Interactomics]]<ref name="Faith2007" /><ref name="Hayete2007" />
*[[Genomics]]
*[[Proteomics]]
*[[Epigenetics]]
* [[Digital morphogenesis]]
* [[Complex adaptive system]]
* [[Multi-agent system]]s
* [[Cognitive Science]]
* [[Pattern oriented modeling]]
* [[Volatility, uncertainty, complexity and ambiguity]]
* [[blue Gene]]
* [[Folding@home]]
* [[Telomerase]]
* [[What Is Life?]]
{{colend}}
==Biographies==
{{colbegin}}
* [[Charles Darwin]]
* [[D'Arcy Thompson]]
* [[William Ross Ashby]]
* [[Ludwig von Bertalanffy]]
* [[Ronald Brown (mathematician)|Ronald Brown]]
* [[Joseph Fourier]]
* [[Brian Goodwin]]
* [[George Karreman]]
* [[Charles S. Peskin]]
* [[Nicolas Rashevsky]]
* [[Robert Rosen (theoretical biologist)|Robert Rosen]]
* [[Anatol Rapoport]]
* [[Rosalind Franklin]]
* [[Francis Crick]]
* [[René Thom]]
* [[Vito Volterra]]
* [[Norbert Wiener]]
{{colend}}
==Notes==
{{Reflist|colwidth=30em}}
===References cited===
* {{cite journal | last1 = Ahmed | first1 = E. | year = 2006 | title = On modeling the immune system as a complex system | url = | journal = Theor. BioSci. | volume = 124 | issue = 3–4| pages = 413–8 | bibcode = 2008arXiv0801.0847A | arxiv = 0801.0847 | doi = 10.1016/j.thbio.2005.07.001 | pmid = 17046369 }}
* Baianu, I. C., Computer Models and Automata Theory in Biology and Medicine., ''Monograph'', Ch.11 in M. Witten (Editor), ''Mathematical Models in Medicine'', vol. 7., Vol. 7: 1513-1577 (1987),Pergamon Press:New York, (updated by Hsiao Chen Lin in 2004 {{ISBN|0-08-036377-6}}
* Bonner, J. T. 1988. ''The Evolution of Complexity by Means of Natural Selection''. Princeton: Princeton University Press.
* Donald Snooks, Graeme, "A general theory of complex living systems: Exploring the demand side of dynamics", ''Complexity'', vol. 13, no. 6, July/August 2008.
* Drazin, P.G., ''Nonlinear systems''. [[Cambridge University Press|C.U.P.]], 1992. {{ISBN|0-521-40668-4}}
* Edelstein-Keshet, L., ''Mathematical Models in Biology''. SIAM, 2004. {{ISBN|0-07-554950-6}}
* Forgacs, G.; S. A. Newman, ''Biological Physics of the Developing Embryo''. C.U.P., 2005. {{ISBN|0-521-78337-2}}
* {{cite journal |author=Israel G |title=On the contribution of Volterra and Lotka to the development of modern biomathematics |journal=History and Philosophy of the Life Sciences |volume=10 |issue=1 |pages=37–49 |year=1988 |pmid=3045853}}
* Israel, G., 2005, "Book on mathematical biology" in [[Ivor Grattan-Guinness|Grattan-Guinness, I.]], ed., ''Landmark Writings in Western Mathematics''. Elsevier: 936-44.
* Jordan, D.W.; Smith, P., ''Nonlinear ordinary differential equations'', 2nd ed. O.U.P., 1987. {{ISBN|0-19-856562-3}}
* Kampen, N.G. van. ''Stochastic Processes in Physics and Chemistry'', North Holland., 3rd ed. 2001, {{ISBN|0-444-89349-0}}
* Murray, J.D., ''Mathematical Biology''. Springer-Verlag, 3rd ed. in 2 vols.: ''Mathematical Biology: I. An Introduction'', 2002 {{ISBN|0-387-95223-3}}; ''Mathematical Biology: II. Spatial Models and Biomedical Applications'', 2003 {{ISBN|0-387-95228-4}}.
* Nicolas Rashevsky. (1938)., ''Mathematical Biophysics''. Chicago: University of Chicago Press.
* Preziosi, L., ''Cancer Modelling and Simulation''. Chapman Hall/CRC Press, 2003. {{ISBN|1-58488-361-8}}.
* Renshaw, E., ''Modelling biological populations in space and time''. C.U.P., 1991. {{ISBN|0-521-44855-7}}
* Rosen, Robert.1991, ''Life Itself: A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life'', Columbia University Press, published posthumously:
* Rosen, Robert .1970. ''Dynamical system theory in biology''. New York, Wiley-Interscience. {{ISBN|0-471-73550-7}}
* Rosen, Robert. 2000, ''Essays on Life Itself'', Columbia University Press.
* Rosen, Robert. 2003, "''Anticipatory Systems; Philosophical, Mathematical, and Methodolical Foundations''", Rosen Enterprises publs.
* Rubinow, S.I., ''Introduction to mathematical biology''. John Wiley, 1975. {{ISBN|0-471-74446-8}}
* {{cite journal |author=Scudo FM |title=Vito Volterra and theoretical ecology |journal=Theoretical Population Biology |volume=2 |issue=1 |pages=1–23 |date=March 1971 |pmid=4950157 |doi=10.1016/0040-5809(71)90002-5}}
* Segel, L.A., ''Modeling dynamic phenomena in molecular and cellular biology''. C.U.P., 1984. {{ISBN|0-521-27477-X}}.
* Strogatz, S.H., ''Nonlinear dynamics and Chaos: Applications to Physics, Biology, Chemistry, and Engineering.'' Perseus, 2001, {{ISBN|0-7382-0453-6}}
* Thompson, D'Arcy W., 1992. ''On Growth and Form''. Dover reprint of 1942, 2nd ed. (1st ed., 1917). {{ISBN|0-486-67135-6}}
==Further reading==
*[https://web.archive.org/web/20160119231346/http://www.kli.ac.at/theorylab/index.html A general list of Theoretical biology/Mathematical biology references, including an updated list of actively contributing authors].
*[http://planetmath.org/?method=l2h&from=objects&id=10746&op=getobj A list of references for applications of category theory in relational biology].
*[http://www.people.vcu.edu/~mikuleck/rosen.htm An updated list of publications of theoretical biologist Robert Rosen]
* [http://homepage.uibk.ac.at/~c720126/humanethologie/ws/medicus/block1/inhalt.html Theory of Biological Anthropology (Documents No. 9 and 10 in English)]
* [http://www.scientistsolutions.com/t5844-Drawing+the+line+between+Theoretical+and+Basic+Biology.html Drawing the Line Between Theoretical and Basic Biology], a forum article by Isidro A. T. Savillo
* {{cite journal|title=Synthesis and Analysis of a Biological System|journal=Genome Informatics Series|number=Sers 10|pages=352–353|oclc=203735966|year=1999|last1=Kurata|first1=Hiroyuki|last2=Taira|first2=K|last3=Kitano|first3=H}}
{{Systems}}
[[Category:Mathematical and theoretical biology]]
Category:Mathematical and theoretical biology
类别: 数学和理论生物学
[[Category:Bioinformatics]]
Category:Bioinformatics
类别: 生物信息学
[[Category:Epidemiology]]
Category:Epidemiology
类别: 流行病学
[[Category:Biostatistics]]
Category:Biostatistics
类别: 生物统计学
[[Category:Biotechnology]]
Category:Biotechnology
类别: 生物技术
[[Category:Complex systems theory]]
Category:Complex systems theory
范畴: 复杂系统理论
[[Category:Systems science]]
Category:Systems science
类别: 系统科学
<noinclude>
<small>This page was moved from [[wikipedia:en:Complex systems biology]]. Its edit history can be viewed at [[复杂系统生物学/edithistory]]</small></noinclude>
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