Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo y học: " Priming nonlinear searches for pathway identification"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: priming nonlinear searches for pathway identification | Theoretical Biology and Medical Modelling BioMed Central Research Priming nonlinear searches for pathway identification Siren R Veflingstad1 2 Jonas Almeida3 and Eberhard O Voit 3 4 Open Access Address Department of Chemistry Biotechnology and Food Science Agricultural University of Norway N-1432 As Norway 2Center for Integrative Genetics Cigene Agricultural University of Norway N-1432 As Norway 3Department of Biostatistics Bioinformatics and Epidemiology Medical University of South Carolina 303K Cannon Place 135 Cannon Street Charleston SC 29425 USA and 4Department of Biochemistry and Molecular Biology Medical University of South Carolina 303K Cannon Place 171 Ashley Avenue Charleston SC 29425 USA Email Siren R Veflingstad - siren.veflingstad@ikbm.nlh.no Jonas Almeida - AlmeidaJ@MUSC.edu Eberhard O Voit - VoitEO@MUSC.edu Corresponding author Published 14 September 2004 Received 12 August 2004 Theoretical Biology and Medical Modelling 2004 1 8 doi 10.1186 1742-4682-1-8 Accepted 14 September 2004 This article is available from http www.tbiomed.cOm content 1 1 8 2004 Veflingstad et al licensee BioMed Central Ltd. This is an open-access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Dense time series of metabolite concentrations or of the expression patterns of proteins may be available in the near future as a result of the rapid development of novel high-throughput experimental techniques. Such time series implicitly contain valuable information about the connectivity and regulatory structure of the underlying metabolic or proteomic networks. The extraction of this information is a challenging task because it usually requires nonlinear estimation methods that involve iterative search algorithms. Priming these algorithms with high-quality initial guesses .