Quantification of degeneracy in biological systems for characterization of functional interactions between modules

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• 作者：Yao Li^a ; ^{yli@math.gatech.edu} ; Gaurav Dwivedi^b ; ^{g.dwivedi@gatech.edu} ; Wen Huang^c ; ^{wenh@mail.ustc.edu.cn} ; Melissa L. Kemp^b ; ^{melissa.kemp@bme.gatech.edu} ; Yingfei Yi^a ; ^d ; ¹ ; ^{yi@math.gatech.edu}
• 关键词：Degeneracy ; Complexity ; Robustness ; Systems biology ; Biological networks
• 刊名：Journal of Theoretical Biology
• 出版年：2012
• 期刊代码：79_00225193
• 类别：mt
• 出版时间：7 June, 2012
• 卷：302
• 期：Complete
• 页码：29-38
• 文件大小：594 K

摘要

There is an evolutionary advantage in having multiple components with overlapping functionality (i.e degeneracy) in organisms. While theoretical considerations of degeneracy have been well established in neural networks using information theory, the same concepts have not been developed for differential systems, which form the basis of many biochemical reaction network descriptions in systems biology. Here we establish mathematical definitions of degeneracy, complexity and robustness that allow for the quantification of these properties in a system. By exciting a dynamical system with noise, the mutual information associated with a selected observable output and the interacting subspaces of input components can be used to define both complexity and degeneracy. The calculation of degeneracy in a biological network is a useful metric for evaluating features such as the sensitivity of a biological network to environmental evolutionary pressure. Using a two-receptor signal transduction network, we find that redundant components will not yield high degeneracy whereas compensatory mechanisms established by pathway crosstalk will. This form of analysis permits interrogation of large-scale differential systems for non-identical, functionally equivalent features that have evolved to maintain homeostasis during disruption of individual components.