Integrating multiple evidence sources to predict transcription factor binding in the human genome

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Integrating multiple evidence sources to predict transcription factor binding in the human genome.

Information about the binding preferences of many transcription factors is known and characterized by a sequence binding motif. However, determining regions of the genome in which a transcription factor binds based on its motif is a challenging problem, particularly in species with large genomes, since there are often many sequences containing matches to the motif but are not bound. Several rul...

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Integrating genomic data to predict transcription factor binding.

Transcription factor binding sites (TFBS) in gene promoter regions are often predicted by using position specific scoring matrices (PSSMs), which summarize sequence patterns of experimentally determined TF binding sites. Although PSSMs are more reliable than simple consensus string matching in predicting a true binding site, they generally result in high numbers of false positive hits. This stu...

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An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding an...

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ژورنال

عنوان ژورنال: Genome Research

سال: 2010

ISSN: 1088-9051

DOI: 10.1101/gr.096305.109