Which ESR1 and PGR binding sites are functional?

Find putative transcription factor binding domains

Repozitorijoje saugomi failai, implementuojantys R Shiny aplikaciją ir leidžiantys vertinti įkeltų genominių duomenų kokybę bei vykdyti biologines analizes.

Transcription Factor (TF) binding preference prediction using deep neural networks.

GIMSAN: motif-finder with biologically realistic and reliable statistical significance analysis

Prediction of transcription factor binding based on DNA sequence

Code for the BMC Genomics paper (Integrating binding and expression data to predict transcription factors combined function)

Gibbs 3.2 formerly located at http://ccmbweb.ccv.brown.edu/gibbs/gibbs.html

A simple genetic algorithm for finding consensus binding sties in DNA sequences in Drosophila

Pipeline for integration different models of transcription factor binding sites

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.

Simple Python parser for MotEvo.

tfNet is a computational tool that identifies putative regulatory regions and genomic signal interactions in a genome-wide scale.

Predicting transcription factor-DNA binding from sequence

Database of HTH-DNA complexes

Artificial neural network to predict transcription factor binding.

ChIP-seq analysis pipeline encompassing data processing, quality control, alignment, peak calling, annotation and motif analysis.

Implementation of BPNet, a base-resolution convolutional neural network for transcription-factor binding prediction, in PyTorch.

A robust statistical test for TF footprint data analyses