書目名稱 | Computational Methods for Estimating the Kinetic Parameters of Biological Systems | 編輯 | Quentin Vanhaelen | 視頻video | http://file.papertrans.cn/233/232715/232715.mp4 | 概述 | Includes cutting-edge techniques.Provides step-by-step details for ease of use.Contains key implementation advice from the experts | 叢書名稱 | Methods in Molecular Biology | 圖書封面 |  | 描述 | This detailed book provides an overview of various classes of computational techniques, including machine learning techniques, commonly used for evaluating kinetic parameters of biological systems. Focusing on three distinct situations, the volume covers the prediction of the kinetics of enzymatic reactions, the prediction of the kinetics of protein-protein or protein-ligand interactions (binding rates, dissociation rates, binding affinities), and the prediction of relatively large set of kinetic rates of reactions usually found in quantitative models of large biological networks. Written for the highly successful .Methods in Molecular Biology. series, chapters include the kind of expert implementation advice that leads to successful results.?.Authoritative and practical, .Computational Methods for Estimating the Kinetic Parameters of Biological Systems. will be of great interest for researchers working through the challenge of identifying the best type of algorithm and who would like to use or develop a computational method for the estimation of kinetic parameters.. | 出版日期 | Book 2022 | 關(guān)鍵詞 | Quantitative mechanistic models; Kinetic parameters; Machine learning; Enzymatic reactions; Protein-liga | 版次 | 1 | doi | https://doi.org/10.1007/978-1-0716-1767-0 | isbn_softcover | 978-1-0716-1769-4 | isbn_ebook | 978-1-0716-1767-0Series ISSN 1064-3745 Series E-ISSN 1940-6029 | issn_series | 1064-3745 | copyright | Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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