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Titlebook: Computational Systems Toxicology; Julia Hoeng,Manuel C. Peitsch Book 2015 Springer Science+Business Media New York 2015 Biological network

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发表于 2025-3-21 19:37:01 | 显示全部楼层 |阅读模式
书目名称Computational Systems Toxicology
编辑Julia Hoeng,Manuel C. Peitsch
视频video
概述Features state-of-the-art computational applications that are crucial for the study of systems toxicology.Includes approaches ranging from data management to mathematical modelling.Gathers key advice
丛书名称Methods in Pharmacology and Toxicology
图书封面Titlebook: Computational Systems Toxicology;  Julia Hoeng,Manuel C. Peitsch Book 2015 Springer Science+Business Media New York 2015 Biological network
描述.This detailed volume explores key state-of-the-art computational applications that are crucial in Systems Toxicology. The recent technological developments in experimental biology and multi-omics measurements that enable Systems Biology and Systems Toxicology can only be fully leveraged by the application of a broad range of computational approaches ranging from data management to mathematical modeling. Taking this into account, chapters in this book cover data management and processing, data analysis, biological network building and analysis, as well as the application of computational methods to toxicological assessment..Written for the .Methods in Pharmacology and Toxicology. series, .Computational Systems Toxicology. includes the kind of key practical advice that will aid readers in furthering our knowledge of toxic substances and reactions to them..
出版日期Book 2015
关键词Biological network models; Computational approaches; Data analysis; Novel biomarkers; Risk assessment; Sa
版次1
doihttps://doi.org/10.1007/978-1-4939-2778-4
isbn_softcover978-1-4939-5003-4
isbn_ebook978-1-4939-2778-4Series ISSN 1557-2153 Series E-ISSN 1940-6053
issn_series 1557-2153
copyrightSpringer Science+Business Media New York 2015
The information of publication is updating

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发表于 2025-3-21 20:25:27 | 显示全部楼层
978-1-4939-5003-4Springer Science+Business Media New York 2015
发表于 2025-3-22 04:29:31 | 显示全部楼层
Computational Systems Toxicology978-1-4939-2778-4Series ISSN 1557-2153 Series E-ISSN 1940-6053
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Marieke de Groot,Jos de Keijser, far from trivial to accurately represent all this knowledge in a format suitable for a wide range of computational analyses. Nevertheless, many research groups have taken up this challenge, inspired by the great value and potential of pathway databases. Nowadays, these databases are routinely used
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https://doi.org/10.1007/978-3-031-43841-7at will contribute to a better biological understanding. Sophisticated computational methods have been developed to separate mathematically the biological signal from the noise in high-throughput datasets; however, visualizing and putting a signal into a relevant biological context using . knowledge
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https://doi.org/10.1007/978-3-031-43841-7enge is to keep the models relevant and representative of current scientific knowledge. Harnessing community intelligence in knowledge curation holds great promise in dealing with the flood of biological information. Another important challenge is to be able to share and communicate networks with ot
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