Network Inference in Molecular Biology - A Hands-on Framework (Paperback, 2012 ed.)

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Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set. Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation. Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.

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Product Description

Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set. Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation. Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.

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Product Details

General

Imprint

Springer-Verlag New York

Country of origin

United States

Series

SpringerBriefs in Electrical and Computer Engineering

Release date

June 2012

Availability

Expected to ship within 10 - 15 working days

First published

2012

Authors

,

Dimensions

235 x 155 x 8mm (L x W x T)

Format

Paperback

Pages

100

Edition

2012 ed.

ISBN-13

978-1-4614-3112-1

Barcode

9781461431121

Categories

LSN

1-4614-3112-3



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