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<font color="#ff8000"> 复杂系统生物学 Complex system biology (CSB)</font>是数学和理论生物学的一个分支或子领域,研究生物有机体结构和功能的复杂性,以及生物和物种的出现与进化,重点研究生物网络及其内部的复杂相互作用,以及生命所必须的基本关系与关系模式。因此,CBS是一个旨在发现和建模生命所必需的关系模式理论科学领域,它只与复杂系统理论和被称为系统生物学的生物学的系统方法有部分重叠;这是因为后者主要局限于生物组织和有机体的简化模型,以及对与生物学复杂性相关的哲学或语义问题的一般性考虑。此外,人们把广泛的抽象理论复杂系统作为应用数学的一个领域进行研究,无论其是否与生物学、化学或物理相关。
 
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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.
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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. 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.
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<font color="#ff8000"> 复杂系统生物学(Complex system biology, CSB)</font>是数学和理论生物学的一个分支或子领域,研究生物有机体结构和功能的复杂性,以及生物和物种的出现与进化,重点研究生物网络及其内部的复杂相互作用,以及对生命至关重要的基本关系和关系模式。因此,CBS是一个理论科学领域,旨在发现和建模生命所必需的关系模式,它只与复杂系统理论有部分重叠,也与生物学的系统方法称为系统生物学;这是因为后者主要局限于生物组织和有机体的简化模型,以及对与生物学复杂性相关的哲学或语义问题的一般性考虑。此外,广泛的抽象理论复杂系统被作为应用数学的一个领域进行研究,无论其是否与生物学、化学或物理相关。
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  --[[用户:Ebteddy|Ebteddy]  ([[用户讨论:Ebteddy:|讨论]])  【审校】“以及对生命至关重要的基本关系和关系模式”改为“以及生命所必须的基本关系与关系模式”
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  --[[用户:Ebteddy|Ebteddy]  ([[用户讨论:Ebteddy:|讨论]])  【审校】“它只与复杂系统理论有部分重叠,也与生物学的系统方法称为系统生物学”改为“它与复杂系统理论以及被称为系统生物学的系统生物学方法只有部分重叠”
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  --[[用户:Thingamabob|Thingamabob]  ([[用户讨论:Thingamabob:|讨论]])  【审校】"因此,CBS是一个理论科学领域,旨在发现和建模生命所必需的关系模式,它只与复杂系统理论有部分重叠,也与生物学的系统方法称为系统生物学"改为“因此,CBS是一个旨在发现和建模生命所必需的关系模式理论科学领域,它只与复杂系统理论和被称为系统生物学的生物学的系统方法有部分重叠"
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  --[[用户:Thingamabob|Thingamabob]  ([[用户讨论:Thingamabob:|讨论]])  【审校】"此外,广泛的抽象理论复杂系统被作为应用数学的一个领域进行研究,无论其是否与生物学、化学或物理相关。"改为"此外,人们把广泛的抽象理论复杂系统作为应用数学的一个领域进行研究,无论其是否与生物学、化学或物理相关。"
      
[[File:Complex-adaptive-system.jpg|right|thumb|276px|Network Representation of a Complex Adaptive System]]
 
[[File:Complex-adaptive-system.jpg|right|thumb|276px|Network Representation of a Complex Adaptive System]]
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Network Representation of a Complex Adaptive System
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一个复杂自适应系统的网络表示
 
一个复杂自适应系统的网络表示
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==生物体和生物圈的复杂性==
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研究人员一直困扰于如何完整定义单个生物体、物种、生态系统、生物进化和生物圈的复杂性,而且这仍然是一个悬而未决的问题。
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==Complexity of organisms and biosphere==
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大多数复杂系统模型通常是根据统计物理学、信息论和非线性动力学的概念来制定的;这些方法并不关注或者说不包括与组织、拓扑属性或代数拓扑有关的复杂性的概念部分,如基因组、交互体和生物有机体的网络连通性这些重要概念。近年来,人们把以信息论、网络拓扑/抽象图论概念为基础的两种互补方法在神经科学和人类认知等领域结合起来。人们普遍认为,组织的复杂程度存在一种应与本体论的现实层次相区别层次结构,现代等级分类的分类方法也承认生物圈的例如:生物领域和生物圈、生物的界、门、纲、目、科、属和种等复杂层次结构。由于生物体具有动态性和组成的可变性、内在的“模糊性”、自生属性、自我繁殖的能力等等,生物体不符合一般系统的“标准”的定义,因此它们在功能和结构上都是“超级复杂”的;因此,在CSB中,生物体只能被定义为一种简单动态系统,“元系统”。这样一个有机体、物种、“生态系统”等等的元系统定义,并不等同于自生系统理论中对系统中的系统的定义。它也不同于K·D·帕尔默在元系统工程中提出的定义,即生物体不同于具有固定输入输出转换函数的机器和自动机,或不同于具有固定相空间的连续动力系统,这与笛卡尔哲学思想相反;因此,尽管“非确定性自动机”和“模糊自动机”也被定义了,但生物体不能仅仅用五组a(状态、启动状态、输入和输出集/字母、转换函数)来定义。然而,棋盘自动机 tessellation automata或元胞自动机 cellular automata 提供了一种直观的、可视化的/计算的视角来洞察较低层次的复杂性,因此已经成为一种越来越流行的离散模型,研究领域包括可计算理论、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。利用遗传算法实现元胞自动机是一个桥接棋盘自动机和CSB中的高层次复杂性方法之间差距的新兴领域。
生物体和生物圈的复杂性
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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]]
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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
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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,而且仍然是一个悬而未决的问题。
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  --[[用户:Thingamabob|Thingamabob]  ([[用户讨论:Thingamabob:|讨论]])  【审校】本段改为"研究人员一直困扰于如何完整定义单个生物体、物种、生态系统、生物进化和生物圈的复杂性,而且这仍然是一个悬而未决的问题“
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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
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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
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大多数复杂系统模型通常是根据统计物理学、信息论和非线性动力学的概念来制定的;然而,这些方法并不关注或不包括与组织、拓扑属性或代数拓扑有关的复杂性的概念部分,如非常重要的基因组、交互体和生物有机体的网络连通性。近年来,以信息论、网络拓扑/抽象图论概念为基础的两种互补方法在神经科学和人类认知领域得到了结合。人们普遍认为,组织的复杂程度存在一种层次结构,应与本体论的现实层次相区别。生物圈的复杂层次结构在现代分类等级分类中也得到承认,例如: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、内在的“模糊性”、自生属性、自我繁殖的能力等等,生物体不符合一般系统的“标准”的定义,因此它们在功能和结构上都是“超级复杂”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”。这样一个有机体、物种、“生态系统”等等的元系统定义,并不等同于Autopoietic系统理论中对系统中的系统的定义。它也不同于k·d·帕尔默在元系统工程中提出的定义,即生物体不同于具有固定输入输出转换函数的机器和自动机,或不同于具有固定相空间的连续动力系统,这与笛卡尔哲学思想相反;因此,尽管“非确定性自动机”和“模糊自动机”也被定义了,但生物体不能仅仅用五组a(状态、启动状态、输入和输出集/字母、转换函数)来定义。然而,棋盘自动机(tessellation automata)或元胞自动机(cellular automata)提供了一种直观的、可视化的/计算的视角来洞察较低层次的复杂性,因此已经成为一种越来越流行的离散模型,研究领域包括可计算理论、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。利用遗传算法实现元胞自动机也是一个新兴的领域,其试图在CSB中填补棋盘自动机与更高层次复杂性方法之间的空白。
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  --[[用户:Ebteddy|Ebteddy]  ([[用户讨论:Ebteddy:|讨论]])  【审校】“k·d·帕尔默”改为“K·D·帕尔默”
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  --[[用户:Ebteddy|Ebteddy]  ([[用户讨论:Ebteddy:|讨论]])  【审校】“生物体只能被定义为简单动态系统的“元系统””改为“生物体只能被定义为一种简单动态系统,“元系统””
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  --[[用户:Ebteddy|Ebteddy]  ([[用户讨论:Ebteddy:|讨论]])  【审校】“并不等同于Autopoietic系统理论“改为”并不等同于自生系统理论“
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  --[[用户:Ebteddy|Ebteddy]  ([[用户讨论:Ebteddy:|讨论]])  【审校】“利用遗传算法实现元胞自动机也是一个新兴的领域,试图在CSB中填补棋盘自动机与更高层次复杂性方法之间的空白。”修改为“利用遗传算法实现元胞自动机是一个桥接棋盘自动机和CSB中的高层次复杂性方法之间差距的新兴领域。”
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  --[[用户:Thingamabob|Thingamabob]  ([[用户讨论:Thingamabob:|讨论]])  【审校】 "然而,这些方法并不关注或不包括与组织、拓扑属性或代数拓扑有关的复杂性的概念部分,如非常重要的基因组、交互体和生物有机体的网络连通性。"改为"这些方法并不关注或者说不包括与组织、拓扑属性或代数拓扑有关的复杂性的概念部分,如基因组、交互体和生物有机体的网络连通性这些重要概念"
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  --[[用户:Thingamabob|Thingamabob]  ([[用户讨论:Thingamabob:|讨论]])  【审校】 “近年来,以信息论、网络拓扑/抽象图论概念为基础的两种互补方法在神经科学和人类认知领域得到了结合。人们普遍认为,组织的复杂程度存在一种层次结构,应与本体论的现实层次相区别。生物圈的复杂层次结构在现代分类等级分类中也得到承认,例如:生物领域和生物圈、生物界、门、生物纲、目、科、属和种。”改为“近年来,人们把以信息论、网络拓扑/抽象图论概念为基础的两种互补方法在神经科学和人类认知等领域结合起来。人们普遍认为,组织的复杂程度存在一种应与本体论的现实层次相区别层次结构,现代等级分类的分类方法也承认生物圈的例如:生物领域和生物圈、生物的界、门、纲、目、科、属和种等复杂层次结构。”
      
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: [[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
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==Topics in complex systems biology==
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==复杂系统生物学的主题==
复杂系统生物学的主题
      
[[File:DNA animation.gif|thumb|right|100px|Animated Molecular Model of a DNA [[double helix]]]]
 
[[File:DNA animation.gif|thumb|right|100px|Animated Molecular Model of a DNA [[double helix]]]]
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Animated Molecular Model of a DNA [[double helix]]
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一个DNA[[双螺旋]]的动画分子模型
 
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一个DNA双螺旋的动画分子模型
      
[[File:Telomerase illustration.jpg|thumb|right|296px|Telomerase structure and function]]
 
[[File:Telomerase illustration.jpg|thumb|right|296px|Telomerase structure and function]]
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Telomerase structure and function
      
端粒酶的结构与功能
 
端粒酶的结构与功能
    
[[File:MAPKpathway diagram.svg|thumb|right|140px|A Complex Signal Transduction Pathway]]
 
[[File:MAPKpathway diagram.svg|thumb|right|140px|A Complex Signal Transduction Pathway]]
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A Complex Signal Transduction Pathway
      
一个复杂的信号转导途径
 
一个复杂的信号转导途径
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The following is only a partial list of topics covered in complex systems biology:
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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涵盖的部分主题列表:
 
以下只是复杂系统生物学所涵盖的部分主题列表:
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