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Báo cáo y học: " Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling"

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: " Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling | BioMed Central Theoretical Biology and Medical Modelling Research Open Access Identification of biomolecule mass transport and binding rate parameters in living cells by inverse modeling Kouroush Sadegh Zadeh Hubert J Montas and Adel Shirmohammadi Address Fischell Department of Bioengineering University of Maryland College Park Maryland 20742 USA Email Kouroush Sadegh Zadeh - kouroush@eng.umd.edu Hubert J Montas - montas@eng.umd.edu Adel Shirmohammadi - ashirmo@umd.edu Corresponding author Published II October 2006 Received 29 August 2006 Theoretical Biology and Medical Modelling 2006 3 36 doi 10.1186 1742-4682-3-36 Accepted 1 1 October 2006 This article is available from http www.tbiomed.com content 3 1 36 2006 Sadegh Zadeh 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 Quantification of in-vivo biomolecule mass transport and reaction rate parameters from experimental data obtained by Fluorescence Recovery after Photobleaching FRAP is becoming more important. Methods and results The Osborne-Moré extended version of the Levenberg-Marquardt optimization algorithm was coupled with the experimental data obtained by the Fluorescence Recovery after Photobleaching FRAP protocol and the numerical solution of a set of two partial differential equations governing macromolecule mass transport and reaction in living cells to inversely estimate optimized values of the molecular diffusion coefficient and binding rate parameters of GFP-tagged glucocorticoid receptor. The results indicate that the FRAP protocol provides enough information to estimate one parameter uniquely using a nonlinear optimization technique. Coupling FRAP experimental data with the inverse modeling strategy one can also uniquely estimate .