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Titlebook: Data Mining Techniques for the Life Sciences; Oliviero Carugo,Frank Eisenhaber Book 2022Latest edition The Editor(s) (if applicable) and T

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51#
發(fā)表于 2025-3-30 12:17:08 | 只看該作者
Deep Mining from Omics Datadely available to researchers. This has afforded clinicians, bioinformaticians, statisticians, and data scientists the opportunity to apply their innovations in feature mining and predictive modeling to a rich data resource to develop a wide range of generalizable prediction models. What has become
52#
發(fā)表于 2025-3-30 13:16:06 | 只看該作者
53#
發(fā)表于 2025-3-30 18:49:16 | 只看該作者
Christian Zinke-Wehlmann,Julia Friedrichw how to cope with the problem of understanding which protein positions may be of interest for biotechnological and biomedical purposes. By applying a consensus procedure, we indicate possible strategies for the result interpretation.
54#
發(fā)表于 2025-3-30 20:59:40 | 只看該作者
55#
發(fā)表于 2025-3-31 03:43:08 | 只看該作者
W. Mulder,P. H. H. Rongen,G. R. Meijerst dedicated software to predict pH-dependent aggregation, and DispHred is the first pH-dependent predictor of protein disorder. Here we dissect the features of these two software applications to train and assist scientists in studying pH-dependent conformational changes in IDPs.
56#
發(fā)表于 2025-3-31 08:23:49 | 只看該作者
IMEx Databases: Displaying Molecular Interactions into a Single, Standards-Compliant Datasette molecular interaction data to the highest caliber, following a detailed curation model and supplying rich metadata by employing common curation rules and harmonized standards. The IMEx Consortium provides comprehensively annotated molecular interaction data integrated into a single, non-redundant, open access dataset.
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