An innovative Positional Pattern Detection tool applied to GAL4 Binding Sites in yeast

Author

Sichtig, Heike ; Riva, Alberto

Author_Institution

Dept. of Mol. Genetics & Microbiol., Univ. of Florida, Gainesville, FL, USA

fYear

2011

fDate

July 31 2011-Aug. 5 2011

Firstpage

2457

Lastpage

2464

Abstract

The computational identification of regulatory elements in genomic DNA is key to understanding the regulatory infrastructure of a cell. We present an innovative tool to identify Transcription Factor Binding Sites (TFBSs) in genomic sequences. We show that our Positional Pattern Detection tool is able to attain high sensitivity and specificity of TFBS detection by capturing dependencies between nucleotide positions within the TFBS, thereby elucidating complex interactions that may be critical for the TFBS activity.

Keywords

biology computing; genetic algorithms; genomics; learning (artificial intelligence); neural nets; pattern recognition; GAL4 yeast binding site; genetic algorithm; genomic DNA; genomic sequence; neural network training; pattern recognition; positional pattern detection tool; spiking neural networks; transcription factor binding sites; Biological cells; Biological neural networks; Delay; Genetic algorithms; Neurons; Pulse width modulation; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2011 International Joint Conference on

Conference_Location

San Jose, CA

ISSN

2161-4393

Print_ISBN

978-1-4244-9635-8

Type

conf

DOI

10.1109/IJCNN.2011.6033538

Filename

6033538