Inference of gene regulatory network using temporal coefficient of determination obtained from ergodic Markov chains

A key problem in Bioinformatics is the inference of gene regulatory networks (GRNs). In many cases, some kind of measure such as mutual information or coefficient of determination (CoD) is used for the inference process. In this paper, we consider the temporal coefficient of determination (tCoD) as a measure of temporal relationship between genes/proteins and we present amethodology to obtain tCoDs from the transition matrix of ergodic Markov chains. The approach described here is applied to the study of the yeast (Saccharomyces cerevisiae) cell cycle. We show preliminary results indicating that tCoDs can be useful when trying to infer GRNs modeled by ergodic Markov chains.