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.
Python library to handle Gene Ontology (GO) terms
Deep functional residue identification
Source ontology files for the Gene Ontology
Schema and generated objects for biolink data model and upper ontology
[ICLR 2022] OntoProtein: Protein Pretraining With Gene Ontology Embedding
python library for working with ontologies and ontology associations
Bio4j abstract model and general entry point to the project
GO enrichment with python -- pandas meets networkx
Function prediction using a deep ontology-aware classifier
📚 Biomedical knowledge mining using GOSemSim and clusterProfiler
Basic and Advanced OBO Graphs: specification and reference implementation
⛳ GO-terms Semantic Similarity Measures
Material for GO OWL/Protege Tutorial
A collection of metadata, tools, and files associated with the Gene Ontology public web presence.
A standalone interactive application for detecting biological significance on a set of genes
Transcripts annotation and GO enrichment Fisher tests
ChIP-seq/RNA-seq analysis software suite for gene expression heatmaps
GeneSCF moved to a dedicated GitHub page, https://github.com/genescf/GeneSCF
Gene ontology (GO) semantic similarity library for Python
The Gene Ontology Helpdesk
Released 1999