Physical Sciences and Mathematics Commons^™

Learning The Structure Of Gene Regulatory Networks From Time Series Gene Expression Data, Haoni Li, Nan Wang, Ping Gong, Edward J. Perkins, Chaoyang Zhang

Faculty Publications

Background: Dynamic Bayesian Network (DBN) is an approach widely used for reconstruction of gene regulatory networks from time-series microarray data. Its performance in network reconstruction depends on a structure learning algorithm. REVEAL (REVerse Engineering ALgorithm) is one of the algorithms implemented for learning DBN structure and used to reconstruct gene regulatory networks (GRN). However, the two-stage temporal Bayes network (2TBN) structure of DBN that specifies correlation between time slices cannot be obtained by score metrics used in REVEAL.

Methods: In this paper, we study a more sophisticated score function for DBN first proposed by Nir Friedman for stationary …