Abstract:
 One of the grand challenges in the future of genomics research is the
 need to develop computational and experimental methods to detect gene-
 gene and gene-environment interactions for identifying the genetic
 contributions to disease and drug response. Scientists have been
 successful in cataloguing genes through genome sequencing projects,
 and we can now generate vast quantities of gene expression data using
 microarrays. However, the biology community has had far less success
 in understanding how genes and proteins are connected and operate
 within networks. When a cell is perturbed (whether by a drug or in a
 disease state), it is important to understand how it will respond in
 terms of gene expression and protein interactions.
 A large volume of current research aims at understanding the
 regulatory connections in a given genetic network. Recent efforts to
 define the components and organization of genetic networks include
 experimental and computational methods to identify putative gene,
 protein and metabolite interactions, global structural properties,
 and regulatory modules and characteristic.
 The objective of the presentation is to illustrate how combined
 experimental and computational apporaches can be used to infer the
 genetic network in which a particular gene of interest is embedded in
 order to understand its function and regulation. During the
 presentation the use of this approach in drug discovery will also be
 illustrated.