tailieunhanh - Báo cáo y học: "Hybrid dynamic/static method for large-scale simulation of metabolism"

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: Hybrid dynamic/static method for large-scale simulation of metabolism | Theoretical Biology and Medical Modelling BioMed Central Research Open Access Hybrid dynamic static method for large-scale simulation of metabolism Katsuyuki Yugit Yoichi Nakayama f Ayako Kinoshita and Masaru Tomita Address Institute for Advanced Biosciences Keio University Fujisawa Kanagawa 252-8520 Japan. Email Katsuyuki Yugi - chaos@ Yoichi Nakayama - ynakayam@ Ayako Kinoshita - ayakosan@ Masaru Tomita - mt@ Corresponding author fEqual contributors Published 04 October 2005 Received 25 April 2005 Theoretical Biology and Medical Modelling 2005 2 42 doi 1742-4682-2-42 Accepted 04 October 2005 This article is available from http content 2 1 42 2005 Yugi et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Many computer studies have employed either dynamic simulation or metabolic flux analysis MFA to predict the behaviour of biochemical pathways. Dynamic simulation determines the time evolution of pathway properties in response to environmental changes whereas MFA provides only a snapshot of pathway properties within a particular set of environmental conditions. However owing to the large amount of kinetic data required for dynamic simulation MFA which requires less information has been used to manipulate large-scale pathways to determine metabolic outcomes. Results Here we describe a simulation method based on cooperation between kinetics-based dynamic models and MFA-based static models. This hybrid method enables quasi-dynamic simulations of large-scale metabolic pathways while drastically reducing the number of kinetics assays needed for dynamic simulations. The dynamic behaviour of metabolic pathways predicted by our .