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4. Genomics, Proteomics and Bioinformatics. Three areas of Life Sciences, bioinformatics, genomics, and proteomics, are driving the current excitement in biomedical research, and are also central to the activities and development of the Center. The availability of complete genomic sequences can now provide all of the genetic components of any organism. Rapidly expanding capabilities to manipulate gene content and expression in microbial and multi-cellular cells and organisms, detect protein-protein interactions, and quantify the activities of macromolecules in vivo suggest the capacity to predict quantitatively the altered behavior of these systems that results from their genetic or pharmacological manipulation. Bioinformatics, as a core discipline, has recently emerged as the size of data sets in biomedical research has increased, as it has become an essential component of this research work. Progress in the new integrative discovery science and systems biology is inconceivable without bioinformatics; i.e., bioinformatics is intrinsic to and irreplaceable in the new paradigm of biomedical research that is now developing in the Center.

5. The Importance of Complexity and Modeling.The research and educational missions of the Center depend upon exploration, understanding and revelation of the complex systems ubiquitous in biology. The study of complex systems depends upon information derived from analysis to identify and characterize the components of the system. However, a simple analysis of isolated components of a system is incapable of detecting, measuring or characterizing emergent properties that derive from the interactions of the components and processes comprising the system. Complexity analyses invoke a nonlinear reconstruction or synthesis of that part of the system under study. This analysis is accomplished by mathematical and computational modeling, or in silico analyses. Applying such modeling strategies is central to the research and educational missions of the Center.

Examples of in silico modeling methods include but are not limited to: a) molecular orbital calculations, molecular electrostatic potential mapping, and topological calculations, b) dynamic simulations based on molecular dynamics and Monte Carlo simulations, c) dynamic systems simulations using cellular automata, and d) high performance computational modeling using large-scale mathematical models (Virtual Parasite Project). These methods generate information about the emergent properties and the perpetual novelty of complex systems.


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Date last modified: 10/27/04
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