Overview of computational methods for the inference of gene regulatory networks

Abstract Increasing volumes of data about the cellular phenotype and classes of intracellular molecules have necessitated the introduction of systemic methods for the analysis of biological systems. These methods bring to focus the integrated nature and complex interactions of biological molecules and processes and, as such, define the emerging field of systems biology. Of the multitude of systems thus analyzed, we provide here an overview of foundational and current methods in the inference of gene regulatory networks (GRNs) and sequence-based pattern discovery. In GRN analysis, the reverse engineering paradigm is given particular attention, including the various types of models (discrete, continuous, hybrid) which may be utilized in reverse engineering a network's structure. Future research directions in these areas are discussed, particularly the potential for ventures that integrate GRN inference, pattern discovery, and experimental methods into a cohesive, productive methodology.