Supplemental material associated with ALife 2020 conference submission.
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Updated
Jun 3, 2020 - HTML
Supplemental material associated with ALife 2020 conference submission.
Automated analysis tool for mutations in promoters, transcription factor binding sites, coding regions and protein domains in the context of gene regulatory networks.
Python Code to extract gene regulatory Information and create Boolean functions from PDFs using OCR and NLP, realized as a Django Website.
Python package for estimating GRNs with Bayesian networks.
Simulation and inference of gene regulatory networks based on transcriptional bursting
An explainable inductive learning model on gene regulatory and toxicogenomic knowledge graph (under development...)
Gene regulatory network reconstruction using random forest regression from only gene expression data from Single Cell RNA Seq Data. This project consisted of feature importance extraction and exploring different methods to investigate different and unique ways to extract feature importance to construct a gene regulatory network.
A Nextflow pipeline demonstrating how to train graph neural networks for gene regulatory network reconstruction using DREAM5 data.
Depicting pseudotime-lagged causality for accurate gene-regulatory inference
Source code for the paper "Fast and Accurate Inference of Gene Regulatory Networks through Robust Precision Matrix Estimation", by Passemiers et al.
TIMEOR: Trajectory Inference and Mechanism Exploration with Omics Data in R
Deciphering driver regulators of cell fate decisions from single-cell RNA-seq data
A R/MATLAB package to construct and compare gene regulatory networks from single-cell transcriptomic data
R package: Simulate Expression data from igraph network using mvtnorm (CRAN; JOSS)
Single-cell Transcriptome and Regulome Analysis Pipeline
Protein Graph Library
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