Evaluation of methods for modeling transcription factor sequence specificity

The most comprehensive analysis to date of models of transcription-factor binding specificity reveals the best methods for predicting in vivo binding from in vitro data. Genomic analyses often involve scanning for potential transcription factor (TF) binding sites using models of the sequence specifi...

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Veröffentlicht in:	Nature biotechnology Jg. 31; H. 2; S. 126 - 134
Hauptverfasser:	Weirauch, Matthew T, Cote, Atina, Norel, Raquel, Annala, Matti, Zhao, Yue, Riley, Todd R, Saez-Rodriguez, Julio, Cokelaer, Thomas, Vedenko, Anastasia, Talukder, Shaheynoor, Bussemaker, Harmen J, Morris, Quaid D, Bulyk, Martha L, Stolovitzky, Gustavo, Hughes, Timothy R
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Nature Publishing Group US 01.02.2013 Nature Publishing Group
Schlagworte:	631/114 631/45/612/822 631/61/191 Agriculture Algorithms analysis Animals Binding sites Bioinformatics Biomedical Engineering/Biotechnology Biomedicine Biotechnology Computational Biology Deoxyribonucleic acid DNA DNA binding proteins DNA sequencing DNA-Binding Proteins - chemistry DNA-Binding Proteins - genetics Genome Genomics Health aspects Life Sciences Mice Nucleotide Motifs - genetics Nucleotide sequencing Physiological aspects Position-Specific Scoring Matrices Protein Array Analysis Proteins Transcription factors Transcription Factors - genetics Transcription Factors - metabolism United States
ISSN:	1087-0156, 1546-1696, 1546-1696
Online-Zugang:	Volltext
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