Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications

ISBN 10: 0195119401 ISBN 13: 9780195119404

Edit� par Oxford University Press, 1999

Langue: anglais

Etat : Neuf Couverture rigide

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D�tails bibliographiques

Titre

Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications

�diteur

Oxford University Press

Date de parution

1999

Langue

anglais

ISBN � 10 chiffres

0195119401

ISBN � 13 chiffres

9780195119404

Reliure

Hardcover

�tat de l'article

New

Catalogues du vendeur

BIOLOGY

A propos de ce titre

Synopsis

This book presents, in one convenient volume, the work of researchers in the field of pattern discovery, a fundamental operation used in the process of extracting knowledge from biomolecular data. The significant growth of the size of biomolecular data has lead scientists to place increasing importance on developing novel techniques for this knowledge extraction. With this fact in mind, the editors have compiled this clear, up-to-date summary of the principle techniques of pattern discovery in molecular biology, in the hope that readers will build on these techniques and make discoveries of their own. The techniques are drawn from many fields of mathematical science, including graph theory, information theory, statistics, and computer vision.

Because there are a variety of equally valid methods of finding patterns, the book presents methods in their purest form so that readers can choose the method or combination that best fits their applications. The contributions are organized into three parts: Finding Patterns in DNA and Protein Sequences; Finding Patterns in 3D Structures, and System Components for Discovery. This resource is essential to anyone who conducts research in biocomputing, and can serve as an excellent supplementary text for biocomputing courses.

Pr�sentation de l'�diteur

This book presents, in one convenient volume, the work of researchers in the field of pattern discovery, a fundamental operation used in the process of extracting knowledge from biomolecular data. The significant growth of the size of biomolecular data has lead scientists to place increasing importance on developing novel techniques for this knowledge extraction. With this fact in mind, the editors have compiled this clear, up-to-date summary of the principle techniques of pattern discovery in molecular biology, in the hope that readers will build on these techniques and make discoveries of their own. The techniques are drawn from many fields of mathematical science, including graph theory, information theory, statistics, and computer vision. Because there are a variety of equally valid methods of finding patterns, the book presents methods in their purest form so that readers can choose the method or combination that best fits their applications. The contributions are organized into three parts: Finding Patterns in DNA and Protein Sequences; Finding Patterns in 3D Structures, and System Components for Discovery. This resource is essential to anyone who conducts research in biocomputing, and can serve as an excellent supplementary text for biocomputing courses.

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