Bioinformatics: Novel Insights from Genomic Information

While scientific methods have dominated research approaches in biology over the past decades, it is increasingly recognized that the complexity of biological systems must be addressed by a different approach, namely unbiased research involving the collection of large amounts of genome-wide information. To enable analysis of this information we and others are developing a variety of computational tools that allow bioinformaticists and wet laboratory biologists to extract novel patterns of data from these results and generate novel biological insights while generating new hypotheses for testing in the laboratory. There are two types of critical tools, databases to collate all information on biomolecules, especially interactions, and tools that reorganize information in a supervised (e.g. pathway analysis or gene ontology) or unsupervised (nonhierarchical clustering and network analysis) manner. Here we describe some of the tools we have developed and how we have used these to gain new ideas in the general area of infection and innate immunity/inflammation. In particular, it is illustrated how such analyses enable novel hypotheses about mechanisms associated with diseases and the mechanisms of action of immunomodulatory and other interventions, the definition of mechanism-based biomarkers/diagnostics, and prospective new interventions based on drug repurposing.