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<p>This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful <i>Methods in Molecular Biology </i>series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.</p><p> Authoritative and cutting-edge, Authoritative and cutting-edge, <i> Computational Methods for Predicting Post-Translational Modification Sites </i>aims to be a useful guide for researchers who are interested in the field of PTM site prediction. </p>
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This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful <i>Methods in Molecular Biology </i>series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.<p> </p><p>Authoritative and cutting-edge, Authoritative and cutting-edge, <i> Computational Methods for Predicting Post-Translational Modification Sites </i>aims to be a useful guide for researchers who are interested in the field of PTM site prediction. </p>
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Computational Methods for Predicting Post-Translational Modification Sites
Editore:
Springer, Berlin|Springer US|Humana, 2022
ISBN 10: 1071623168
ISBN 13: 9781071623169
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Da: moluna, Greven, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues relate. Codice articolo 551453263
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Computational Methods for Predicting Post-Translational Modification Sites (Methods in Molecular Biology, 2499)
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Computational Methods for Predicting Post-Translational Modification Sites
Print on DemandDa: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successfulMethods in Molecular Biologyseries, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.Authoritative and cutting-edge,Authoritative and cutting-edge,Computational Methods for Predicting Post-Translational Modification Sites aimsto be ausefulguide for researchers who are interested in the field of PTM site prediction. 344 pp. Englisch. Codice articolo 9781071623169
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Computational Methods for Predicting Post-Translational Modification Sites
Editore:
Springer US, Springer US Jun 2022, 2022
ISBN 10: 1071623168
ISBN 13: 9781071623169
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Buch. Condizione: Neu. Neuware -This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.Authoritative and cutting-edge, Authoritative and cutting-edge, Computational Methods for Predicting Post-Translational Modification Sites aims to be a useful guide for researchers who are interested in the field of PTM site prediction.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 344 pp. Englisch. Codice articolo 9781071623169
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Computational Methods for Predicting Post-Translational Modification Sites
Da: AHA-BUCH GmbH, Einbeck, Germania
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successfulMethods in Molecular Biologyseries, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.Authoritative and cutting-edge,Authoritative and cutting-edge,Computational Methods for Predicting Post-Translational Modification Sites aimsto be ausefulguide for researchers who are interested in the field of PTM site prediction. Codice articolo 9781071623169
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Computational Methods for Predicting Post-Translational Modification Sites (Methods in Molecular Biology, 2499)
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
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Condizione: New. Codice articolo ABLIING23Mar2317530223896
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