Multiple Alignments, Hidden Markov Models and SVMs (Paperback)

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Remote protein homology detection is a problem of detecting evolutionary relationship between proteins at low sequence similarity level. Among several problems in remote protein homology detection include the questions of determining which combination of multiple alignment and classification techniques is the best as well as the misalignment of protein sequences during the alignment process. Therefore, this study deals with remote protein homology detection via assessing the impact of using structural information on protein multiple alignments over sequence information. This study further presents the best combinations of multiple alignment and classification programs to be chosen. This study also improves the quality of the multiple alignments via integration of a refinement algorithm.

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Product Description

Remote protein homology detection is a problem of detecting evolutionary relationship between proteins at low sequence similarity level. Among several problems in remote protein homology detection include the questions of determining which combination of multiple alignment and classification techniques is the best as well as the misalignment of protein sequences during the alignment process. Therefore, this study deals with remote protein homology detection via assessing the impact of using structural information on protein multiple alignments over sequence information. This study further presents the best combinations of multiple alignment and classification programs to be chosen. This study also improves the quality of the multiple alignments via integration of a refinement algorithm.

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Product Details

General

Imprint

Lap Lambert Academic Publishing

Country of origin

Germany

Release date

2012

Availability

Expected to ship within 10 - 15 working days

First published

2012

Authors

,

Dimensions

229 x 152 x 10mm (L x W x T)

Format

Paperback - Trade

Pages

164

ISBN-13

978-3-8473-3171-1

Barcode

9783847331711

Categories

LSN

3-8473-3171-X



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