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- W2144967110 abstract "We formulate a probabilistic framework for transcription factor (TF) binding prediction that is built on the standard position specific frequency matrix (PSFM) and higher order Markovian background models. Contrary to the traditional hypothesis testing based methods which report a significance (p) value of TF binding at every possible base pair position in a promoter sequence, we develop a probabilistic methodology to assess TF binding to whole promoter sequences. Performance of the proposed method is demonstrated via simulations." @default.
- W2144967110 created "2016-06-24" @default.
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- W2144967110 date "2007-06-01" @default.
- W2144967110 modified "2023-09-25" @default.
- W2144967110 title "Probabilistic Framework for Transcription Factor Binding Prediction" @default.
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- W2144967110 doi "https://doi.org/10.1109/gensips.2007.4365834" @default.
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