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Updated: Jun 12, 2026

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

FuncBase: a resource for quantitative gene function annotation.

John E Beaver¹, Murat Tasan, Francis D Gibbons

¹Department of Biological Chemistry & Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA.

Bioinformatics (Oxford, England)

|May 25, 2010

Summary

This summary is machine-generated.

FuncBase provides quantitative gene function predictions using machine learning, aiding researchers in prioritizing experiments. This web resource offers fungal and mammalian gene annotations with community feedback and evidence visualization.

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Published on: December 22, 2017

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Gene function prediction is crucial for experimental resource allocation.
Existing methods may lack quantitative, machine learning-based annotations.
Access to comprehensive gene function data is essential for biological research.

Purpose of the Study:

To introduce FuncBase, a web resource for quantitative gene function annotations.
To provide machine learning-based functional predictions for fungal and mammalian genes.
To integrate a community feedback system and visualize evidence for annotations.

Main Methods:

Development of a web resource (FuncBase) for gene function prediction.
Application of machine learning algorithms for quantitative gene function annotation.
Integration of Gene Ontology (GO) terms for standardized functional classification.
Implementation of a community feedback system for annotation refinement.
Development of a Cytoscape viewer for functional linkage graph visualization.

Main Results:

FuncBase offers quantitative, machine learning-based gene function annotations.
Annotations cover fungal and mammalian genes, linked to Gene Ontology terms.
The resource includes a community feedback system and visualizations of supporting evidence.
Functional linkage graphs are accessible via a custom Cytoscape viewer.

Conclusions:

Computational gene function prediction, as implemented in FuncBase, effectively focuses experimental efforts.
FuncBase serves as a valuable web resource for accessing and evaluating quantitative gene function annotations.
The integrated evidence and community feedback enhance the utility and reliability of gene function predictions.