Pattern Discovery for Deciphering Gene Regulation : with Evolutionary Computation and Data Mining Based Methods

Language: English

Published by VDM Verlag Dr. Müller, 2011

3639362799 / 9783639362794

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Transcription Factor (TF) and Transcription Factor Binding Site (TFBS) bindings are fundamental protein-DNA interactions in transcriptional regulation. TFs and TFBSs are conserved to form patterns (motifs) due to their important roles for controlling gene expressions and finally affecting functions and appearances. Pattern discovery is thus important for deciphering gene regulation, which has tremendous impacts on the understanding of life, bio-engineering and therapeutic applications. This thesis contributes to pattern discovery involving TFBS motifs and TF-TFBS associated sequence patterns based on Evolutionary Computation (EC), especially Genetic Algorithms (GAs), which are promising for bioinformatics problems with huge and noisy search space. On TFBS motif discovery, three novel GA based algorithms are developed, namely GALF-P with focus on optimization, GALF-G for modeling, and GASMEN for spaced motifs. TF-TFBS associated sequence pattern (rule) discovery is further investigated for better deciphering protein-DNA interactions in regulation. We for the first time generalize previous exact TF-TFBS rules to approximate ones using a progressive approach.

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Title
Pattern Discovery for Deciphering Gene Regulation : with Evolutionary Computation and Data Mining Based Methods
Author
Tak-Ming Chan
Publisher
VDM Verlag Dr. Müller
Publication year
2011
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3639362799
ISBN 13
9783639362794
Item weight
209 grams
Dimensions
220x150x9 mm

AHA-BUCH GmbH

Einbeck, Germany

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AbeBooks seller since August 14, 2006

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