A Decision Support System for Reverse Engineering Gene Regulatory Networks

Abstract

In this paper we present a knowledge-based system that aims at helping scientists in the reverse engineering process of gene regulatory networks. The main motivation of the proposed approach is to support scientists in the choice of the wide variety of algorithms and methods currently applied in the literature to infer Gene Regulatory Networks starting from gene expression measured using microarray technology. The Decision Support System (DSS) architecture is based on an ontology to model the knowledge base, a logical reasoner that builds the workflow of tasks to be done starting from the user’s request and a set of rules, and, finally, an agenda that runs the algorithms and software scheduled by the logical reasoner. The Decision Support System allows the interaction with the user in order to show intermediate results, refine the results and enrich the knowledge base with new expertise.