系统生物学
基因调控网络
计算机科学
时间序列
基因
系列(地层学)
生物系统
基因表达谱
数据科学
作者
Ziv Bar-Joseph,Anthony Gitter,Itamar Simon
摘要
Biological processes are often dynamic, thus researchers must monitor their activity at multiple time points. The most abundant source of information regarding such dynamic activity is time-series gene expression data. These data are used to identify the complete set of activated genes in a biological process, to infer their rates of change, their order and their causal effects and to model dynamic systems in the cell. In this Review we discuss the basic patterns that have been observed in time-series experiments, how these patterns are combined to form expression programs, and the computational analysis, visualization and integration of these data to infer models of dynamic biological systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI