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Bioinformation Discovery: Data to Knowledge in Biology
Bioinformation Discovery: Data to Knowledge in Biology
Bioinformation Discovery: Data to Knowledge in Biology
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Bioinformation Discovery: Data to Knowledge in Biology

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This new edition continues to illustrate the power of biological data in knowledge discovery. It describes biological data types and representations with examples for creating a workflow in bioinformation discovery. The concepts in knowledge discovery from data are illustrated using line diagrams. The principles and concepts in knowledge discovery are used for the development of prediction models for simulations of biological reactions and events. Advanced topics in molecular evolution and cellular & molecular biology are addressed using bioinformation gleaned through discovery. Each chapter contains approximately 10 exercises for practice. This will help students to expand their problem solving skills in Bioinformation Discovery. In this new edition, there are three new chapters covering single nucleotide polymorphism, genes, proteins and disease, and protein functions driven by surface electrostatics. 

LanguageEnglish
PublisherSpringer
Release dateSep 1, 2018
ISBN9783319953274
Bioinformation Discovery: Data to Knowledge in Biology

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    Bioinformation Discovery - Pandjassarame Kangueane

    © Springer International Publishing AG, part of Springer Nature 2018

    Pandjassarame KangueaneBioinformation Discoveryhttps://doi.org/10.1007/978-3-319-95327-4_1

    1. Bioinformatics for Bioinformation

    Pandjassarame Kangueane¹ 

    (1)

    Pondicherry, India

    Abstract

    This chapter introduces concepts in bioinformatics and describes its application in agriculture, healthcare, and biotechnology. The principles and components of bioinformatics are discussed in detail. A sound knowledge on the basic concepts in bioinformatics is the foundation for bioinformation discovery from data. The significance of bioinformation discovery in defining targets for developing drugs is discussed. The issues in a discovery environment under pharmaceutical or biotechnological research and development environment are illustrated using block diagrams. The importance of biological data (sequence, structure, and function) in discovery is highlighted. The chapter also contains sufficient exercise problems for

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