生物
特质
基因表达
表达式(计算机科学)
表型
基因
疾病
功能(生物学)
自然选择
计算生物学
进化生物学
遗传学
选择(遗传算法)
计算机科学
内科学
人工智能
医学
程序设计语言
作者
Xifan Wang,Yanling Hao,Xiaoxue Liu,Shoujuan Yu,Weibo Zhang,Songtao Yang,Zhengquan Yu,Fazheng Ren
标识
DOI:10.1016/j.jgg.2019.03.015
摘要
Understanding how gene expression is translated to phenotype is central to modern molecular biology, and the success is contingent on the intrinsic tractability of the specific traits under examination. However, an a priori estimate of trait tractability from the perspective of gene expression is unavailable. Motivated by the concept of entropy in a thermodynamic system, we here propose such an estimate (ST) by gauging the number (N) of expression states that underlie the same trait abnormality, with large ST corresponding to large N. By analyzing over 200 yeast morphological traits, we show that ST predicts the tractability of an expression-trait relationship. We further show that ST is ultimately determined by natural selection, which builds co-regulated gene modules to minimize possible expression states.
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