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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Multi-state modeling of biomolecules ： ウィキペディア英語版 Multi-state modeling of biomolecules Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behaviour of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: The problem of how to describe and specify a multi-state system (the "specification problem") and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem"). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states, and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus,〔Danos V, Laneve C. (2004) Formal molecular biology. Theoretical Computer Science 325:69-110.〕 BioNetGen,〔Faeder JR, Blinov ML, Goldstein B, Hlavacek, WS. (2005) Rule-Based Modeling of Biochemical Networks. Complexity 10(4):22-41.〕 the Allosteric Network Compiler and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm.〔〔 Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators further fall into two categories: Non-spatial simulators such as StochSim,〔Le Novère N, Shimizu TS. STOCHSIM: modelling of stochastic biomolecular processes. Bioinformatics 17(6):575-576〕 DYNSTOC, RuleMonkey, and NFSim and spatial simulators, including Meredys, SRSim〔〔 and MCell.〔Stiles JR, Bartol TM (2001). Computational Neuroscience: Realistic Modeling for Experimentalists. In: De Schutter, E (ed). Computational Neuroscience: Realistic Modeling for Experimentalists. CRC Press, Boca Raton.〕 Modelers can thus choose from a variety of tools; the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future. == Introduction == 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Multi-state modeling of biomolecules」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.