FungiFun: a web-based application for functional categorization of fungal genes and proteins

Steffen Priebe; Jörg Linde; Daniela Albrecht; Reinhard Guthke; Axel A Brakhage

doi:10.1016/j.fgb.2010.11.001

FungiFun: a web-based application for functional categorization of fungal genes and proteins

Fungal Genet Biol. 2011 Apr;48(4):353-8. doi: 10.1016/j.fgb.2010.11.001. Epub 2010 Nov 10.

Authors

Steffen Priebe¹, Jörg Linde, Daniela Albrecht, Reinhard Guthke, Axel A Brakhage

Affiliation

¹ Research Group Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology-Hans-Knöll-Institute (HKI), Jena, Germany. steffen.priebe@hki-jena.de

PMID: 21073976
DOI: 10.1016/j.fgb.2010.11.001

Abstract

FungiFun assigns functional annotations to fungal genes or proteins and performs gene set enrichment analysis. Based on three different classification methods (FunCat, GO and KEGG), FungiFun categorizes genes and proteins for several fungal species on different levels of annotation detail. It is web-based and accessible to users without any programming skills. FungiFun is the first tool offering gene set enrichment analysis including the FunCat categorization. Two biological datasets for Aspergillus fumigatus and Candida albicans were analyzed using FungiFun, providing an overview of the usage and functions of the tool. FungiFun is freely accessible at https://www.omnifung.hki-jena.de/FungiFun/.

Publication types

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

MeSH terms

Aspergillus fumigatus / genetics
Candida albicans / genetics
Computational Biology / methods*
Fungal Proteins / genetics*
Fungal Proteins / physiology*
Genes, Fungal*
Internet*

Substances

Fungal Proteins