ChIP-seq analysis notes from Ming Tang
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Updated
Aug 5, 2024 - Python
ChIP-seq analysis notes from Ming Tang
A repository with exploration into using transformers to predict DNA ↔ transcription factor binding
Transcription Factor Binding Prediction from ATAC-seq and scATAC-seq with Deep Neural Networks
A multimodal model predicting chromatin-associated proteins binding on the human genome.
Motif discovery for DNA sequences using multiobjective optimization and genetic programming.
Artificial neural network to predict transcription factor binding.
Implementation of BPNet, a base-resolution convolutional neural network for transcription-factor binding prediction, in PyTorch.
Transcription Factor (TF) binding preference prediction using deep neural networks.
Simple Python parser for MotEvo.
Which ESR1 and PGR binding sites are functional?
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.
A simple genetic algorithm for finding consensus binding sties in DNA sequences in Drosophila
Pipeline for integration different models of transcription factor binding sites
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