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

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

pyJASPAR: A Pythonic interface to JASPAR transcription factor motifs

Fast Inference of Networks from Directed Regulations

Co-accessibility network from single-cell ATAC-seq data. Python code, based on Cicero package (R).

An R package for multi-dimensional pathway enrichment analysis

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

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

Code and data used by the JASPAR profile inference tool

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

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

Depicting pseudotime-lagged causality for accurate gene-regulatory inference

A powerful abstraction of gene databases

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

CREST-seq peak calling.

Meta-analysis of DNA methylation in ART

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