Novel statistical methodology for FDR(False Discovery Rate) analysis of Gene Regulatory Networks
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Updated
Nov 5, 2024 - Python
Novel statistical methodology for FDR(False Discovery Rate) analysis of Gene Regulatory Networks
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.
biopatternsg is a system that builds gene regulatory networks from a basic collection of biological objects, gathering and processing PubMed abstracts, using Internet available informational resources like Mesh, GeneOntology, UniProt, PDB and others, and that uses java and logical engines like prolog to integrate and analyse them.
CUDA code for DE+PSO for Gene Regulatory Network inference
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.
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 package implements a benchmarking of several gene network inference algorithms from gene expression data
Condition-Specific Gene Regulatory Network construction
a novel method of gene regulatory network structure inference
SCANet is a python package that incorporates the inference of gene co-expression networks from single-cell gene expression data
Diffusion model for gene regulatory network inference.
scMEGA: Single-cell Multiomic Enhancer-based Gene regulAtory network inference
Prediction of key transcription factors in cell fate determination using enhancer networks. See full ANANSE documentation for detailed installation instructions and usage examples.
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).
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