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12918_2012_926_MOESM 2_ESM.pdf

12918_2012_926_MOESM2_ESM.pdf

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DREM 2.0 uses a logistic function to incorporate transcription factor (TF) gene expression levels into the learning of the classifier in the input-output hidden Markov model (IOHMM). The expression ratio of a TF between two time points is used to scale the binding value of the TF on a gene. The function outputs values in the range [-1,1] to allow for negative influence in the case of underexpression. The user can define a minimum threshold for the expression level of a TF.

The study collected protein-DNA interaction data sets for D. Melanogaster, A. thaliana, human, and mouse. For human, the data was obtained from the ENCODE consortium and included 126 unique TFs and 954,378 static protein-DNA interactions. Ranked human PWM-gene predictions were also obtained and resulted in 59,578 interactions.

The study assessed TF binding prediction at split nodes with DECOD and found that it was able to predict 10 out of 24 identified TF families (42%). The predicted motifs were matched to known TF matrices in TRANSFAC using STAMP.

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DREM 2.0 uses a logistic function to incorporate transcription factor (TF) gene expression levels into the learning of the classifier in the input-output...

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File Format: PDF
File Size: 519 KB
Pages: 13
Language: EN
Total Downloads: 51
Last Updated: 2 months ago

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