Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process

摘要

BackgroundCausal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning these networks is challenging due to the low sample size and high dimensionality of genomic data.