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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key...

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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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

Maxat Kulmanov¹, Fernando Zhapa-Camacho¹, Robert Hoehndorf¹

¹Computational 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.

Nucleic Acids Research

|May 21, 2021

Summary

DeepGOPlus uses deep learning to predict protein functions from sequences. DeepGOWeb provides these predictions via a website and API, ensuring accuracy and Gene Ontology consistency.

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Last Updated: Nov 4, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

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An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

Molecular Biology
Bioinformatics
Computational Biology

Background:

Understanding protein function is essential for deciphering molecular mechanisms in biology.
The number of available protein sequences far exceeds experimental investigation capacity.
Accurate protein function prediction is critical for biological research.

Purpose of the Study:

To present DeepGOPlus, a novel deep learning-based method for protein function prediction.
To introduce DeepGOWeb, a user-friendly platform for accessing DeepGOPlus predictions.
To enable interoperability with Semantic Web-enabled biological databases.

Main Methods:

DeepGOPlus utilizes deep learning algorithms combined with sequence similarity analysis.
DeepGOWeb offers predictions through a web interface, an API, and SPARQL query language.
The method ensures predictions align with the structured framework of the Gene Ontology.

Main Results:

DeepGOWeb provides accurate and rapid protein function predictions.
The platform can predict functions for any protein and any term within the Gene Ontology.
Predictions are consistent with established biological knowledge represented in the Gene Ontology.

Conclusions:

DeepGOPlus and DeepGOWeb offer a powerful and accessible tool for protein function prediction.
The platform facilitates biological research by bridging the gap between sequence data and functional understanding.
DeepGOWeb enhances data integration in bioinformatics through Semantic Web technologies.