This repository contains code and datasets related to entity/knowledge papers from the VERT (Versatile Entity Recognition & disambiguation Toolkit) project, by the Knowledge Computing group at Microsoft Research Asia (MSRA).

Prediction of key transcription factors in cell fate determination using enhancer networks. See full ANANSE documentation for detailed installation instructions and usage examples.

scMEGA: Single-cell Multiomic Enhancer-based Gene regulAtory network inference

Diffusion model for gene regulatory network inference.

a novel method of gene regulatory network structure inference

Official Implementation of Context-Dependent Gene Regulatory Networks (CDGRNs)

SCANet is a python package that incorporates the inference of gene co-expression networks from single-cell gene expression data

This is a repository for creating a UAV network based on the GRN graph using python.

This package implements a benchmarking of several gene network inference algorithms from gene expression data

Condition-Specific Gene Regulatory Network construction

An experiment to tag ner entities related with biological molecular species using spaCy, fine-tuning a spacy's pipeline, and building a knowledge base of regulatory events, in order to model a gene regulatory network from them.

This project combines Generative AI and Logic AI to form an integrated process, a pipeline, that retrieves large volumes of scientific information and produces logical models that can be validated and leveraged by human experts. Our goals are to organize and to analyze knowledge with the assistance of AI and other bio-information retrieval tools.

python version of NestBoot-FDR

A tool for visualizing gene regulatory networks

This repository provides a model of the MAPK and Akt pathways. Parameters and initial values are mainly based on biological assumptions. The model is therefore conceptual, and the purpose is to get a better understanding of the interactions between genes, that are important in some cancers.

An experiment to tag ner entities related with biological molecular species using spaCy, fine-tuning a spacy's pipeline, and building a knowledge base of regulatory events, in order to model a gene regulatory network.

CUDA code for DE+PSO for Gene Regulatory Network inference

Novel statistical methodology for FDR(False Discovery Rate) analysis of Gene Regulatory Networks

Rodrigo García-Valiente, Elena Merino, Antoine van Kampen. ABM of the germinal center with implementation of SHM fate tree, sequence representation and PC/MBC gene network.

Inferring GRN from scRNA-seq data.