Discovering gene regulatory networks through combination of diverse large-scale biological evidence

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A major challenge in current post-genome molecular biology and bioinformatics research is to fully understand gene regulation: how and when each and every gene is switched on and off during the life of the cell, particularly in response to changing environmental or cellular states. Gene regulation is essential to organism survival, and deciphering how genes are regulated is critical for understanding genetic misregulation, a major cause of disease and developmental malformations. Deciphering gene regulation is a reverse-engineering problem. The goal is to understand how a system (in this case the cell) works from experimental evidence. To this end, biologists disturb the inputs (changes in the environment or genetic alterations) and monitor the outputs (for example, measurements of relative abundance of genes in the cell). Distinct measurements of the outputs represent aspects of the same regulatory mechanism and can be combined to formulate accurate models of gene regulation. These models are usually called gene regulatory or transcriptional networks.