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Titlebook: Biological Networks and Pathway Analysis; Tatiana V. Tatarinova,Yuri Nikolsky Book 2017 Springer Science+Business Media LLC 2017 Protein-p

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樓主: Daguerreotype
51#
發(fā)表于 2025-3-30 09:11:10 | 只看該作者
52#
發(fā)表于 2025-3-30 13:35:02 | 只看該作者
Book 2017ble, comprehensive, and cutting-edge, .Biological Networks and Pathway Analysis .presents both “wet lab” experimental methods and computational tools in order to cover a broad spectrum of issues in this fascinating new field..
53#
發(fā)表于 2025-3-30 17:03:18 | 只看該作者
https://doi.org/10.1007/978-3-476-02897-6man-readable biological networks with a structured syntax are a powerful way of representing biological information generated from high-density data. This article presents sbv IMPROVER, a crowd-verification approach for the visualization and expansion of biological networks.
54#
發(fā)表于 2025-3-30 21:17:30 | 只看該作者
?Nichts Drittes … in der Natur??s annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.
55#
發(fā)表于 2025-3-31 02:33:43 | 只看該作者
56#
發(fā)表于 2025-3-31 06:53:13 | 只看該作者
sbv IMPROVER: Modern Approach to Systems Biology,man-readable biological networks with a structured syntax are a powerful way of representing biological information generated from high-density data. This article presents sbv IMPROVER, a crowd-verification approach for the visualization and expansion of biological networks.
57#
發(fā)表于 2025-3-31 12:48:44 | 只看該作者
Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways,s annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.
58#
發(fā)表于 2025-3-31 16:21:25 | 只看該作者
Comprehensive Analyses of Tissue-Specific Networks with Implications to Psychiatric Diseases,ion to statistical and combinatorial issues in data analyses. This chapter describes computational approaches developed by us and the others to tackle challenges in tissue-specific network analyses, with the main focus on psychiatric diseases.
59#
發(fā)表于 2025-3-31 20:02:28 | 只看該作者
60#
發(fā)表于 2025-3-31 22:25:48 | 只看該作者
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