🧬 Generative modeling of regulatory DNA sequences with diffusion probabilistic models 💨
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Updated
Oct 10, 2024 - Python
🧬 Generative modeling of regulatory DNA sequences with diffusion probabilistic models 💨
Elucidating the Utility of Genomic Elements with Neural Nets
surrogate quantitative interpretability for deepnets
Data-driven design of context-specific regulatory elements
Genomic sequence preprocessing toolkit
lsgkm+gkmexplain with regression functionality. Builds off kundajelab/lsgkm (which has gkmexplain), which in turn builds off Dongwon-Lee/lsgkm (the original lsgkm repo)
squid repository for manuscript analysis
Threshold and p-value computations for Position Weight Matrices
Interpreting sequence-to-function machine learning models
Deep learning model for non-coding regulatory variants
A set of tutorials for how to use all the tools in ML4GLand
Deep Unfolded Convolutional Dictionary Learning for motif discovery.
A curated list of regulatory genomics papers and resources.
Datasets for benchmarking, testing and developing in EUGENe
A Hugo-based deployment of biocomputeobject.org
Analyze the active regulatory region of DNA using FFNN and CNN
Repository documenting applications of the ML4GLand suite on published datasets
Motif representation and analysis toolkit in Python
Prediction of transcription factor binding based on DNA sequence
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