Database of HTH-DNA complexes
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Updated
Aug 23, 2015 - Mathematica
Database of HTH-DNA complexes
GIMSAN: motif-finder with biologically realistic and reliable statistical significance analysis
Artificial neural network to predict transcription factor binding.
Motif discovery for DNA sequences using multiobjective optimization and genetic programming.
Find putative transcription factor binding domains
Which ESR1 and PGR binding sites are functional?
Parse TF motifs from public databases, read into R, and scan using 'rtfbs'.
tfNet is a computational tool that identifies putative regulatory regions and genomic signal interactions in a genome-wide scale.
BiasAway will improve TFBS enrichment analyses and the applied analysis of ChIP-Seq data, particularly for the annotation of reliable TFBSs within ChIP-Seq peaks.
An R package for de novo discovery of enriched DNA motifs (e.g. TFBS)
Gibbs 3.2 formerly located at http://ccmbweb.ccv.brown.edu/gibbs/gibbs.html
A robust statistical test for TF footprint data analyses
A simple genetic algorithm for finding consensus binding sties in DNA sequences in Drosophila
Python bindings for the TFM-Pvalue program.
Code for the BMC Genomics paper (Integrating binding and expression data to predict transcription factors combined function)
Scripts for motif assessment for HOCOMOCO v10/v11.
Prediction of transcription factor binding based on DNA sequence
Simple Python parser for MotEvo.
DNA Transcription Factor Binding Prediction (Self-learning Project)
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