Event Date/Time: Jun 16, 2003 End Date/Time: Jun 19, 2003
Registration Date: Mar 28, 2003
Early Registration Date: Feb 14, 2003
Abstract Submission Date: May 09, 2003
Paper Submission Date: May 09, 2003
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A major bottleneck in drug discovery remains the consolidation of data and the reduction of noise from large-scale gene and protein expression studies. Computational methods have been used to explore the inherent complexity in biology and form the basis of a comprehensive framework that is critical to honing in on disease targets and their binding sites. The data-intensive approach to leveraging information from disparate databases will produce a framework for exploring biological pathways and the molecular relationships within those pathways. This infrastructure requires an interoperability of multiple databases, as well as the integration of key reference points such as time parameters, clinical conditions, and patient data. Strategies for accomplishing data reduction and gaining insight into identifying druggable leads will be discussed

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Beyond Genome 2003 will also feature programs on Bioinformatics, RNAi, and Systems Biology

Sponsoring Publication:
CHI's Prospects for Commercialization of Human Monoclonal Antibodies

As protein identification and characterization technologies are improving, the bottleneck is shifting from generating proteomic information to applying it. CHI's Seventh Annual Proteomics conference will highlight the latest developments in protein profiling and functional proteomics, with greatest emphasis placed on deriving maximum value from the generated information in therapeutic and diagnostic development

RNA interference (RNAi) is a powerful, highly conserved process by which sequence-specific RNA selectively targets and silences gene expression in plants and animals post-transcription. Potentially, this process has major implications for drug development and drug target validation. This meeting will address the latest basic and applied research tools, techniques, and methods to explore RNAi and its potential role in these ways. It will also compare RNAi with other knock-out and knock-down tools for target validation.

Advances in genomics and proteomics have increased our understanding of biological systems at the molecular level. Systems Biology modeling can elucidate how individual system components interact, integrate, and function to form a complex organism. Examples of computational modeling, in conjunction with empirical research, are providing a greater understanding of disease states and target prioritization. This combination may increase the probability of successful drug development. This conference will bring together experts from life and computational sciences to discuss the state of the field. Anyone interested in Systems Biology tools, methods, and concepts to develop or improve drug development strategies should attend this conference.


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San Diego
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