Python library to handle Gene Ontology (GO) terms
-
Updated
May 5, 2024 - Python
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
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
GO enrichment with python -- pandas meets networkx
Function prediction using a deep ontology-aware classifier
Transcripts annotation and GO enrichment Fisher tests
Gene ontology (GO) semantic similarity library for Python
Unsupervised neural network for learning embeddings of GO terms.
scripts for parsing PDB, fasta, and GO
Genome-wide gene gain/loss mapping tool using DTL(Duplication-Transfer-Loss) reconciliation method
A tool for non-coding genomic regions function enrichment analysis based on Regulatory Elements Gene Ontology Annotation (RE-GOA)
A powerful abstraction of gene databases
This is the repository for reproducing results in "APRILE: Exploring the Molecular Mechanisms of Drug Side Effects with Explainable Graph Neural Networks".
molecular graph representation
Protein function prediction through latent tensor reconstruction
Stochastic Gene Ontology Enrichment Analyses (GOEA) Simulations in manscript + Multiple-Test Correction Simulations
A tool for non-coding genomic regions function enrichment analysis based on Regulatory Elements Gene Ontology Annotation (RE-GOA)
Released 1999