Isbn: 9789819982530 - association analysis techniques and applications in bioinformatics (2 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2025

    9819982537 / 9789819982530

    • Softcover

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    EUR 149,10

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    Taschenbuch. Zustand: Neu. Association Analysis Techniques and Applications in Bioinformatics | Qingfeng Chen | Taschenbuch | xxi | Englisch | 2025 | Springer | EAN 9789819982530 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Sprache: Englisch

    Verlag: Springer, 2025

    9819982537 / 9789819982530

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Zustand: Neu

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    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis.This book offers an essential introduction to the theoretical and practical aspects of association analysis, including data pre-processing, data mining methods/algorithms, and tools that are widely applied for computational biology. It covers significant recent advances in the field, both foundational and application-oriented, helping readers understand the basic principles and emerging techniques used to discover interesting association patterns in diverse and heterogeneous biology data, such as structure-function correlations, and complex networks with gene/protein regulation.The main results and approaches are described in an easy-to-follow way and accompanied by sufficientreferences and suggestions for future research. This carefully edited monograph is intended to provide investigators in the fields of data mining, machine learning, artificial intelligence, and bioinformatics with a profound guide to the role of association analysis in computational biology. It is also very useful as a general source of information on association analysis, and as an overall accompanying course book and self-study material for graduate students and researchers in both computer science and bioinformatics.