FunTaxIS-lite: a simple and light solution to investigate protein functions in all living organisms

Author:

Bianca Federico1,Ispano Emilio1,Gazzola Ermanno1,Lavezzo Enrico1,Fontana Paolo2,Toppo Stefano1ORCID

Affiliation:

1. Computational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova , Padova, Italy

2. Research and Innovation Center, Edmund Mach Foundation, San Michele all'Adige , Trento, Italy

Abstract

Abstract Motivation Defining the full domain of protein functions belonging to an organism is a complex challenge that is due to the huge heterogeneity of the taxonomy, where single or small groups of species can bear unique functional characteristics. FunTaxIS-lite provides a solution to this challenge by determining taxon-based constraints on Gene Ontology (GO) terms, which specify the functions that an organism can or cannot perform. The tool employs a set of rules to generate and spread the constraints across both the taxon hierarchy and the GO graph. Results The taxon-based constraints produced by FunTaxIS-lite extend those provided by the Gene Ontology Consortium by an average of 300%. The implementation of these rules significantly reduces errors in function predictions made by automatic algorithms and can assist in correcting inconsistent protein annotations in databases. Availability and implementation FunTaxIS-lite is available on https://www.medcomp.medicina.unipd.it/funtaxis-lite and from https://github.com/MedCompUnipd/FunTaxIS-lite.

Funder

Ministero dell’Istruzione, dell’Università e della Ricerca, PON

Università degli Studi di Padova, Italy

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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