ProbTF provides a flexible and principled probabilistic framework to predict transcription factor binding from multiple data sources. ProbTF uses the standard position specific frequency matrix (PSFM) and the d:th order Markovian background models as its building blocks (this choice is arbitrary though, and similar methods can be implemented using other models as well). In addition, ProbTF can incorporate basically any genome-level information (i.e., information at the level of individual nucleotides) in a probabilistic manner to estimate binding probabilities.
Prof. (pro term) Harri Lähdesmäki, D.Sc. (Tech)
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Harri Lähdesmäki, Alistair G. Rust and Ilya Shmulevich,
Probabilistic inference of transcription factor binding from multiple data sources,
PLoS ONE, Vol. 3, No. 3, e1820, 2008.