ChIP-seq analysis notes from Ming Tang
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Updated
May 24, 2024 - Python
ChIP-seq analysis notes from Ming Tang
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
Haystack: Epigenetic Variability and Transcription Factor Motifs Analysis Pipeline
A repository with exploration into using transformers to predict DNA ↔ transcription factor binding
Parse TF motifs from public databases, read into R, and scan using 'rtfbs'.
Transcription Factor Binding Prediction from ATAC-seq and scATAC-seq with Deep Neural Networks
Python bindings for the TFM-Pvalue program.
ReMapEnrich is a R-software package to identify significantly enriched regions from ReMap catalogues or user defined catalogues. ReMapEnrich provide functions to import any in-house catalogue, automate and plot the enrichment analysis for genomic regions.
An R package for de novo discovery of enriched DNA motifs (e.g. TFBS)
A robust statistical test for TF footprint data analyses
tfNet is a computational tool that identifies putative regulatory regions and genomic signal interactions in a genome-wide scale.
Artificial neural network to predict transcription factor binding.
An R package designed to integrate and visualize various levels of epigenomic information, including but not limited to: ChIP, Histone, ATAC, and RNA sequencing. epiRomics is also designed to identify enhancer and enhanceosome regions from these data.
Which ESR1 and PGR binding sites are functional?
Dual threshold optimization for identifying convergent evidence: TF binding locations and TF perturbation responses.
Prediction of the binding specificity of transcription factors using support vector regression
Database of HTH-DNA complexes
pyJASPAR: A Pythonic interface to JASPAR transcription factor motifs
Simple Python parser for MotEvo.
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