Data challenge with kernel methods - MVA MSc

Discover transcription factor (TF) binding specificities/sites (TFBS) using binding site motif sequence and structural information.

A Python package to generate prior gene regulatory networks.

Prediction of the binding sites of multiple transcription factors in a whole genome

CRAFT: Cellular Reprogramming Analysis with Integrated Framework and Mechanistic Insight

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.

Scans TF binding sites based on motifs.

Published in GigaScience. Web app for post-GWAS/QTL analysis that performs a slew of novel bioinformatics analyses to cross-reference GWAS/QTL mapping results with a host of publicly available rice databases

MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets

Patterns of Binding Targets

Bioinformatics study on tfbs and their association with specific tissues.

An integrative toolkit for detecting cell type-specific regulators

Unofficial fork of the DeepSEA deep learning genomics project

Dual threshold optimization for identifying convergent evidence: TF binding locations and TF perturbation responses.

An ensemble method for predicting transcription factor in protein sequences

Motif discovery for DNA sequences using multiobjective optimization and genetic programming.

Bioinformatic approach to identify functional transcription factor binding motifs