A nearly new copy, square and tight with no creases or splits, just ever so lightly shelf-rubbed. Contents fresh and clean, not showing any pen-marks. Looks and feels unread. Thus a tidy book in very presentable condition.

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D�tails bibliographiques

Titre

Computational Text Analysis: For Functional Genomics and Bioinformatics

�diteur

Oxford University Press

Date de parution

2006

Langue

anglais

ISBN � 10 chiffres

0198567413

ISBN � 13 chiffres

9780198567417

Reliure

Paperback

�dition

First Edition.

�tat de l'article

Like New

Catalogues du vendeur

Science, Mathematics & Technology

A propos de ce titre

Synopsis

This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply impossible.
Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically "read" the literature on all the genes. Including background chapters on the necessary biology, statistics and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science.

Pr�sentation de l'�diteur

This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis, and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself -- for thousands of genes it is simply impossible! Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically "read" the literature on all the genes. Including background chapters on the necessary biology, statistics, and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science.

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