A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

Code for the paper "Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts"

Detecting Regulatory Elements using GRO-seq and PRO-seq

pyJASPAR: A Pythonic interface to JASPAR transcription factor motifs

Single-cell RNA-seq data-based inference of multilayer inter- and intra-cellular signaling networks

Co-accessibility network from single-cell ATAC-seq data. Python code with AnnData, based on Cicero algorithm.

Fast Inference of Networks from Directed Regulations

Code and data used to create the JASPAR UCSC Genome Browser tracks data hub

An R package for multi-dimensional pathway enrichment analysis

A “data light” TF-network mapping algorithm using only gene expression and genome sequence data.

Analysis of regulatory impacts of autism-associated SNPs on biological pathways in the fetal and adult cortex.

Integrated workflow to predict super-enhancers and compute feature importance

A powerful abstraction of gene databases

Code and data used by the JASPAR profile inference tool

Crosstalk between codon optimality and 3' UTR cis-elements dictates mRNA stability

target: An R Package to Predict Combined Function of Transcription Factors

CARTMAN: Co-occurrence Analysis of Repeating Transcription-factor Motifs And Networks

Scanning sample-specific miRNA regulation from bulk and single-cell RNA-sequencing data

All code generated for Loupe et al. 2023