Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling

Ee 6902 Mathematical Modeling of Gene Regulatory

Gene regulatory network inference: an introductory survey

Gene regulatory networks are powerful abstractions of biological systems. Since the advent of high-throughput measurement technologies in biology in the late 90s, reconstructing the structure of such networks has been a central computational problem in systems biology. While the problem is certainly not solved in its entirety, considerable progress has been made in the last two decades, with ma...

Kernel-based Gene Regulatory Network Inference

We propose a kernel-based method for inferring regulatory networks from gene expression data that exploits several important factors previously neglected in the literature, including expression clustering, nonlinear regulator-gene relationships, variable time lags and gene competition. In particular, our approach infers regulatory relationships by encouraging genes with similar expression patte...

Network inference, analysis, and modeling in systems biology.

Improving gene regulatory network inference using network topology information.

Inferring the gene regulatory network (GRN) structure from data is an important problem in computational biology. However, it is a computationally complex problem and approximate methods such as heuristic search techniques, restriction of the maximum-number-of-parents (maxP) for a gene, or an optimal search under special conditions are required. The limitations of a heuristic search are well kn...