DeepGOWeb: fast and accurate protein function prediction on the (Semantic) Web

Maxat Kulmanov; Fernando Zhapa-Camacho; Robert Hoehndorf

doi:10.1093/nar/gkab373

DeepGOWeb: fast and accurate protein function prediction on the (Semantic) Web

Nucleic Acids Res. 2021 Jul 2;49(W1):W140-W146. doi: 10.1093/nar/gkab373.

Authors

Maxat Kulmanov¹, Fernando Zhapa-Camacho¹, Robert Hoehndorf¹

Affiliation

¹ Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.

Abstract

Understanding the functions of proteins is crucial to understand biological processes on a molecular level. Many more protein sequences are available than can be investigated experimentally. DeepGOPlus is a protein function prediction method based on deep learning and sequence similarity. DeepGOWeb makes the prediction model available through a website, an API, and through the SPARQL query language for interoperability with databases that rely on Semantic Web technologies. DeepGOWeb provides accurate and fast predictions and ensures that predicted functions are consistent with the Gene Ontology; it can provide predictions for any protein and any function in Gene Ontology. DeepGOWeb is freely available at https://deepgo.cbrc.kaust.edu.sa/.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Deep Learning
Gene Ontology
Internet
Proteins / chemistry
Proteins / genetics
Proteins / physiology*
Sequence Analysis, Protein / methods*
Software*

Substances

Proteins