Thermodynamic principles for system biology and the patterns of flower pigmentation.

IF 1.3 4区 生物学 Q3 BIOLOGY Theory in Biosciences Pub Date : 2022-09-01 Epub Date: 2022-07-20 DOI:10.1007/s12064-022-00372-y
Qinyi Zhao
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引用次数: 1

Abstract

The thermodynamic principles for system biology are reviewed and formulated, and then basic patterns of flower pigmentation are interpreted. Main thoughts: (1) any biological trait (color or function of a cell) is logically related to a thermodynamic system (or physiological system, signaling network of the cell), (2) the striped, speckled and circle are three basic patterns of flower pigmentation, the development of flowers is an irreversible process, (3) the patterns of flower pigmentation are formed in flower development, (4) the flower cells can change its color in a period of development and this process is controlled thermodynamically, (5) there is giant space of physiology within an organism and within its numerous thermal states can appear under different conditions. In this theory, the dominant inheritance means that a gene contributes great to the thermodynamic stability of a trait related system; different genes can be interacted or integrated thermodynamically according to their contribution to the stability of its related system. By combination of Turing theory and our views, complex patterns of pigmentation could be explained theoretically.

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系统生物学的热力学原理和花色素沉着的模式。
综述并阐述了系统生物学的热力学原理,阐述了花色素沉着的基本规律。主要思想:(1)任何生物学特性(细胞的颜色或功能)在逻辑上都与一个热力学系统(或细胞的生理系统、信号网络)有关;(2)条纹、斑点和圆形是花色素沉着的三种基本模式,花的发育是一个不可逆的过程;(3)花色素沉着的模式是在花的发育过程中形成的;(4)花细胞在一个发育时期内可以改变颜色,这一过程是受热力学控制的。(5)在一个有机体内部有巨大的生理空间,在它的众多热状态中可以出现在不同的条件下。在这一理论中,显性遗传意味着一个基因对性状相关系统的热力学稳定性贡献很大;不同的基因可以根据其对相关系统稳定性的贡献而在热力学上相互作用或整合。将图灵理论与我们的观点相结合,可以从理论上解释色素沉着的复杂模式。
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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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Clustering systems of phylogenetic networks. MLACNN: an attention mechanism-based CNN architecture for predicting genome-wide DNA methylation. A biosemiotic interpretation of certain genital morphological structures in the spiders Dysdera erythrina and Dysdera crocata (Araneae: Dysderidae). On a population model with density dependence and Allee effect. Matrix stability and bifurcation analysis by a network-based approach.
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