Combined RNA and ATAC Footprint Training of Gene Regulatory Network
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Updated
Sep 4, 2026 - R
Combined RNA and ATAC Footprint Training of Gene Regulatory Network
Command-first ATAC-seq footprinting, motif analysis, and reproducible interactive reports
🧬 Generative modeling of regulatory DNA sequences with diffusion probabilistic models 💨
CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.
One interface to nine genomic deep-learning oracles — variant effect prediction, calibrated per-track percentiles, and plain-English analysis through MCP.
Elucidating the Utility of Genomic Elements with Neural Nets
surrogate quantitative interpretability for deepnets
Robust and efficient analysis of single-cell perturbation studies
Genomic sequence preprocessing toolkit
A unified framework for discovering, analyzing, integrating, and visualizing regulatory motifs and transcription factor binding sites across bulk, single-cell, and long-read sequencing modalities.
Interpretable machine learning system for discovering hidden regulatory switches in non-coding DNA using ENCODE genomic data. Optimized for resource-constrained, reproducible research.
Data-driven design of context-specific regulatory elements
lsgkm+gkmexplain with regression functionality. Builds off kundajelab/lsgkm (which has gkmexplain), which in turn builds off Dongwon-Lee/lsgkm (the original lsgkm repo)
A set of tutorials for how to use all the tools in ML4GLand
Pipeline: Identification of cis-regulatory elements by matrix scoring and analysis of supporting empirical biological data.
Interpreting sequence-to-function machine learning models
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
Integrative framework combining TF footprinting with genome-wide association analyses to identify causal noncoding variants and elucidate their regulatory mechanisms in gene regulation
A curated list of regulatory genomics papers and resources.
NCypher — honest, context-specific triage of non-coding regulatory variants in paediatric DMG. Built with Claude: Life Sciences (Researcher track).
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