Candidate OPC–endothelial cell interactors
-
Updated
May 3, 2016 - Jupyter Notebook
The mission of the GO Consortium is to develop a comprehensive, computational model of biological systems, ranging from the molecular to the organism level, across the multiplicity of species in the tree of life.
The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. This knowledge is both human-readable and machine-readable, and is a foundation for computational analysis of large-scale molecular biology and genetics experiments in biomedical research.
Candidate OPC–endothelial cell interactors
Bio4j abstract model and general entry point to the project
GOfreq: GO prediction by BLAST and PSIBLAST sequence search
R Package for Gene Ontology Label Discernment and Identification.
Material for GO OWL/Protege Tutorial
ChIP-seq/RNA-seq analysis software suite for gene expression heatmaps
Kay Prüfer’s FUNC — a package for detecting significant associations between gene sets and ontological annotations
Gene ontology (GO) semantic similarity library for Python
This module is responsible for displaying reports from Gene Ontology (GO) analyses. This module contains a Gene Ontology Annotation Format (GAF) file loader to import GO terms assigned to features. Otherwise, GO assignments must already be loaded into the Tripal database using other data loaders (e.g. using the Tripal InterPro Analysis module or…
Set of small R scripts helpful in various bioinformatics projects
An R package for RNA-seq DGE downstream automation and clustering analysis
This is a version of topGO using roxygen2 and Rmd
A Bio2BEL package for converting the Gene Ontology (GO) to BEL
GO Term Visualizations
Python and R programs used in the identification of repurposed drugs against viruses responsible for causing epidemics/pandemics
GO enrichment with python -- pandas meets networkx
Released 1999