transcription-factor-binding

There are 38 repositories under transcription-factor-binding topic.

  • crazyhottommy/ChIP-seq-analysis

    ChIP-seq analysis notes from Ming Tang

    Language:Python8216412307

  • MAGICS-LAB/DNABERT_2

    [ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome

    Language:Shell4201214088

  • lucidrains/tf-bind-transformer

    A repository with exploration into using transformers to predict DNA ↔ transcription factor binding

    Language:Python86809

  • pinellolab/haystack_bio

    Haystack: Epigenetic Variability and Transcription Factor Motifs Analysis Pipeline

    Language:HTML473711
  • maxATAC

    MiraldiLab/maxATAC

    Transcription Factor Binding Prediction from ATAC-seq and scATAC-seq with Deep Neural Networks

    Language:Python2958611

  • Danko-Lab/rtfbs_db

    Parse TF motifs from public databases, read into R, and scan using 'rtfbs'.

    Language:R232328

  • remap-cisreg/ReMapEnrich

    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.

    Language:HTML154155

  • j-andrews7/pytfmpval

    Python bindings for the TFM-Pvalue program.

    Language:C++9225

  • saketkc/moca

    :m: Tool for motif conservation analysis

    Language:PostScript910

  • MyersGroup/MotifFinder

    An R package for de novo discovery of enriched DNA motifs (e.g. TFBS)

    Language:R7202

  • mbelmadani/motifgp

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

    Language:Python6230
  • epiRomics

    Huising-Lab/epiRomics

    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.

    Language:HTML5192

  • BrentLab/Dual_Threshold_Optimization

    Dual Threshold Optimization compares two ranked lists of features (e.g. genes) to determine the rank threshold for each list that minimizes the hypergeometric p-value of the overlap of features. It then calculates a permutation based empirical p-value and an FDR

    Language:Rust4111

  • VorontsovIE/diHOCOMOCO

    Scripts for motif assessment for HOCOMOCO v10/v11.

    Language:Ruby4200

  • draeger-lab/SABINE

    Prediction of the binding specificity of transcription factors using support vector regression

    Language:Java3232

  • mahossam/DNA-Transcription-Factor-Binding-Prediction

    DNA Transcription Factor Binding Prediction (Self-learning Project)

    Language:Jupyter Notebook3101

  • asntech/jaspar

    Source code for JASPAR web portal and REST API

    Language:JavaScript2211

  • christacaggiano/neural-net

    Artificial neural network to predict transcription factor binding.

    Language:Python2202

  • dohlee/bpnet-pytorch

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

    Language:Python220

  • kchu25/MotifPvalue.jl

    Threshold and p-value computations for Position Weight Matrices

    Language:Julia2140

  • UcarLab/BiFET

    A robust statistical test for TF footprint data analyses

    Language:R2452

  • aqlaboratory/hth-dna-db

    Database of HTH-DNA complexes

    Language:Mathematica1201

  • brlauuu/motevowrapper

    Simple Python parser for MotEvo.

    Language:Python12160

  • jawa23bio/ChIP-Seq

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

    1100

  • komorowskilab/tfNet

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

    Language:C#1202

  • tanlabcode/FCOP

    Language:C++110

  • ytabatabaee/TF_Binding_Prediction

    Predicting transcription factor-DNA binding from sequence data

    Language:Jupyter Notebook1000

  • zanarashidi/transcription-factor-binding

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

    Language:Python1100

  • akshayparopkari/BiasAway

    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.

    Language:Python0100

  • BCMSLab/target_ranking

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

    Language:R0100

  • dansta0804/TF_analysis

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

    Language:R0100

  • gibbs-hmm/Gibbs-Motif-Sampler

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

    Language:C0000

  • lincoln-harris/motifScan

    Find putative transcription factor binding domains

    Language:C++0000

  • ScienceMoo/DNA_structure_ML

    Prediction of transcription factor binding based on DNA sequence

    Language:Jupyter Notebook0100

  • ubercomrade/MultiDeNA

    Pipeline for integration different models of transcription factor binding sites

    Language:Python0100

  • tbrunetti/ConSeGA

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

    Language:Python10