Editore: WSPC, 2025
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Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, SG, 2025
ISBN 10: 9819807174 ISBN 13: 9789819807178
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Aggiungi al carrelloHardback. Condizione: New. This book presents a curated collection of research articles from the Journal of Bioinformatics and Computational Biology, highlighting advances in protein-protein interaction-based computational methods for predicting protein complexes, host-pathogen interactions (HPIs), and protein functions. In Part I, it addresses the dynamic challenges of protein complex prediction using innovative techniques like GECA and IPC-RPIN, which integrate network topology, gene expression, and GO annotations to improve accuracy, especially for small complexes. Part II focuses on HPIs, reviewing computational approaches, predictive models, and tools that enhance understanding of infectious diseases, with a particular emphasis on machine learning applications. Part III delves into protein function prediction, employing PPI networks, multi-label methods, and iterative models that account for dynamic interactions. Collectively, these studies provide a comprehensive resource for advancing computational biology and understanding cellular and disease mechanisms.
Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, 2025
ISBN 10: 9819807174 ISBN 13: 9789819807178
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Aggiungi al carrelloHardcover. Condizione: Brand New. 300 pages. 3.94x3.94x2.36 inches. In Stock.
Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, SG, 2025
ISBN 10: 9819807174 ISBN 13: 9789819807178
Da: Rarewaves.com UK, London, Regno Unito
EUR 137,59
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Aggiungi al carrelloHardback. Condizione: New. This book presents a curated collection of research articles from the Journal of Bioinformatics and Computational Biology, highlighting advances in protein-protein interaction-based computational methods for predicting protein complexes, host-pathogen interactions (HPIs), and protein functions. In Part I, it addresses the dynamic challenges of protein complex prediction using innovative techniques like GECA and IPC-RPIN, which integrate network topology, gene expression, and GO annotations to improve accuracy, especially for small complexes. Part II focuses on HPIs, reviewing computational approaches, predictive models, and tools that enhance understanding of infectious diseases, with a particular emphasis on machine learning applications. Part III delves into protein function prediction, employing PPI networks, multi-label methods, and iterative models that account for dynamic interactions. Collectively, these studies provide a comprehensive resource for advancing computational biology and understanding cellular and disease mechanisms.
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Aggiungi al carrelloBuch. Condizione: Neu. COMPUTATIONAL APPROACHES IN MOLECULAR INTERACTION ANALYSIS | Wong Limsoon | Buch | Englisch | 2025 | World Scientific | EAN 9789819807178 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 121,35
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a curated collection of research articles from the Journal of Bioinformatics and Computational Biology, highlighting advances in protein-protein interaction-based computational methods for predicting protein complexes, host-pathogen interactions (HPIs), and protein functions. In Part I, it addresses the dynamic challenges of protein complex prediction using innovative techniques like GECA and IPC-RPIN, which integrate network topology, gene expression, and GO annotations to improve accuracy, especially for small complexes. Part II focuses on HPIs, reviewing computational approaches, predictive models, and tools that enhance understanding of infectious diseases, with a particular emphasis on machine learning applications. Part III delves into protein function prediction, employing PPI networks, multi-label methods, and iterative models that account for dynamic interactions. Collectively, these studies provide a comprehensive resource for advancing computational biology and understanding cellular and disease mechanisms.