复杂系统生物学

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 system biology （CSB）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。

Network Representation of a Complex Adaptive System

一个复杂自适应系统的网络表示

生物体和生物圈的复杂性

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。 A complete definition of complexity for individual organisms, species, ecosystems, biological evolution and the biosphere has eluded researchers, and still is an ongoing issue.

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。

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 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, 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 is also an emerging field attempting to bridge the gap between the tessellation automata and the higher level complexity approaches in CSB.

复杂系统生物学的主题

一个DNA双螺旋的动画分子模型

端粒酶的结构与功能

一个复杂的信号转导途径

以下只是复杂系统生物学所涵盖的部分主题列表:

• 生物与物种的关系与进化 Organisms and species relations and evolution
• 物种间的相互作用 Interactions among Species
• 进化论和种群遗传学 Evolution theories and population genetics
  • 群体遗传学模型 Population genetics models
  • 表观遗传学 Epigenetics
  • 分子进化理论 Molecular evolution theories
• 量子生物计算学Quantum biocomputation

• Quantum genetics

量子遗传

• Relational biology

关系生物学

• Self-reproduction (also called self-replication in a more general context)

自我繁殖(在更一般的情况下也称为自我复制)

• 计算基因模型 Computational gene models
  • DNA拓扑学 DNA topology
  • DNA测序理论 DNA sequencing theory
• 进化发育生物学 Evolutionary developmental biology
• 自我生产 Autopoiesis
• 蛋白质折叠 Protein folding
• 端粒酶在体内的构象和功能 Telomerase conformations and functions in vivo
• 表观遗传学 Epigenetics
• 交互组学 Interactomics

• 细胞信号传导 Cell signaling

• 信号转导网络 Signal transduction networks

• 复杂神经网络 Complex neural nets

• 基因网络 Genetic networks

• 形态发生 Morphogenesis

• 数字形态发生 Digital morphogenesis

• 复杂自适应系统 Complex adaptive systems

• 形态形成的拓扑模型 Topological models of morphogenesis

• 渔业种群动态 Population dynamics of fisheries

• 流行病学 Epidemiology

• 理论生态学 Theoretical ecology

• 免疫系统 Immune system

另请参阅

• 数学和理论生物学 Mathematical and theoretical biology

• 抽象关系生物学 Abstract relational biology

• 复杂 Complexity

• 复杂系统 Complex system

• 生物系统 Biological system

• 系统理论 Systems theory

• 动力系统 Dynamical system

• 动力系统理论 Dynamical systems theory

• 自动机理论 Automata theory

• 元胞自动机 Cellular automaton

• 系统生物学Systems biology

• 人类学中的系统理论 Systems theory in anthropology

• 自组织 Self-organization

• 非线性度 Nonlinearity

• 生成科学 Generative sciences

• 紧急情况 Emergence

• 生物圈 Biosphere

• 脱氧核糖核酸 DNA

• 量子生物学 Quantum biology

• • 量子遗传学 Quantum genetics

• • 量子生物化学 Quantum biochemistry

• • 量子化学 Quantum chemistry

• • 量子分子动力学 Quantum molecular dynamics

• 蛋白质折叠 Protein folding

• 交互组学 Interactomics

• 基因组学 Genomics

• 蛋白质组学 Proteomics

• 表观遗传学 Epigenetics

• 数字形态 Digital morphogenesis

• 复杂自适应系统 Complex adaptive system

• 多代理系统 Multi-agent systems

• 认知科学 Cognitive Science

• 面向模式的建模 Pattern oriented modeling

• 波动性，不确定性，复杂性和歧义性 Volatility, uncertainty, complexity and ambiguity

• 蓝色基因 blue Gene

• 折叠@家 Folding@home

• 端粒酶 Telomerase

• 生命是什么 What Is Life?

传记

• Charles Darwin

• D'Arcy Thompson

• William Ross Ashby

• Ludwig von Bertalanffy

• Ronald Brown

• Joseph Fourier

• Brian Goodwin

• George Karreman

• Charles S. Peskin

• Nicolas Rashevsky

• Robert Rosen

• Anatol Rapoport

• Rosalind Franklin

• Francis Crick

• René Thom

• Vito Volterra

• Norbert Wiener

笔记

参考文献引用

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进一步阅读

• A general list of Theoretical biology/Mathematical biology references, including an updated list of actively contributing authors.

• A list of references for applications of category theory in relational biology.

• An updated list of publications of theoretical biologist Robert Rosen

• Theory of Biological Anthropology (Documents No. 9 and 10 in English)

• Drawing the Line Between Theoretical and Basic Biology, a forum article by Isidro A. T. Savillo

• Kurata, Hiroyuki; Taira, K; Kitano, H (1999). "Synthesis and Analysis of a Biological System". Genome Informatics Series (Sers 10): 352–353. OCLC 203735966.