Biocomplexity VII: Unraveling the Function and Kinetics

Schnell, Santiago

Abstract

This proposal requests partial funding for the workshop """"""""Biocomplexity VII: Unraveling the Function and Kinetics of Biochemical Networks: From Experiments to Systems Biology,"""""""" organized by the Biocomplexity Institute and the School of Informatics at Indiana University. The Biocomplexity workshop series aims to be broader in scope and more interdisciplinary than other workshops and conferences in this area, while each workshop remains focused on a clearly defined problem. Biocomplexity VII will bring together researchers in many disciplines (including experimental and theoretical biology, biophysics, engineering, mathematics and computer science) to discuss current and future problems in the reconstruction, kinetics and function of biological networks. High-throughput experimental assays play a major role in the current shift from reductionist to systems approaches to biological sciences problems. The data sets these experiments generate promise to identify the components and interactions of regulatory biochemical networks. The Biocomplexity VII workshop aims to bring together specialists in a broad array of methodologies to see how they can combine to explicate the functions of genes and proteins in a network context by developing mathematical and computational approaches suited for the analysis of high-throughput data sets. The objectives of the workshop are to: (i) To explore and present the development of new experimental and theoretical approaches for the purposes of reconstructing complex biochemical networks; (ii) To promote interaction between engineers, physicists, mathematicians, biologists, and chemists with interests in all aspects of reconstructing complex biochemical networks, and (iii) To provide a forum for junior faculty and graduate students to interact with a wide range of experts. The methodologies the workshop will discuss will apply to any organism, including humans, where only three to five percent of genes have identified functions. Understanding the function of genes and proteins in a network context, will improve our ability to predict and control their responses to internal and external perturbations. For the foreseeable future, the type of modeling predictions will likely be one of the many inputs into the decision making process in the pharmaceutical industry, and medical treatments. The proceeding and discussion of conference will be published in a peer-refereed journal.