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2005
IEEE

Discriminative Discovery of Transcription Factor Binding Sites from Location Data

9 years 5 months ago
Discriminative Discovery of Transcription Factor Binding Sites from Location Data
Motivation: The availability of genome-wide location analyses based on chromatin immunoprecipitation (ChIP) data gives a new insight for in silico analysis of transcriptional regulations. Results: We propose a novel discriminative discovery framework for precisely identifying transcriptional regulatory motifs from both positive and negative samples (sets of upstream sequences of both bound and unbound genes by a transcription factor (TF)) based on the genome-wide location data. In this framework, our goal is to find such discriminative motifs that best explain the location data in the sense that the motifs precisely discriminate the positive samples from the negative ones. First, in order to discover an initial set of discriminative substrings between positive and negative samples, we apply a decision tree learning method which produces a text-classification tree. We extract several clusters consisting of similar substrings from the internal nodes of the learned tree. Second, we sta...
Yuji Kawada, Yasubumi Sakakibara
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where CSB
Authors Yuji Kawada, Yasubumi Sakakibara
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