Kniha Pattern Discovery for Deciphering Gene Regulation Tak-Ming Chan

Pattern Discovery for Deciphering Gene Regulation

with Evolutionary Computation and Data Mining Based Methods

Autor: Tak-Ming Chan
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: VDM Verlag
Dostupnost: U nakladatele na objednávku
Odesíláme za 17-27 dnů
1 407
Transcription Factor (TF) and Transcription Factor Binding Site (TFBS) bindings are fundamental prot...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2011
Stránek
144
EAN
9783639362794
ISBN
3639362799
Enbook ID
06843150
Vydavatel
Hmotnost
222
Rozměry
152 x 229 x 9

Kompletní popis

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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