Evidence map›Paper›PMID 37672040›Full record

ArticleBioinformatics (Oxford, England)2023

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

Federico Bianca, Emilio Ispano, Ermanno Gazzola, Enrico Lavezzo, Paolo Fontana, Stefano Toppo

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Federico BiancaComputational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy.
Emilio IspanoComputational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy.
Ermanno GazzolaComputational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy.
Enrico LavezzoComputational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy.
Paolo FontanaResearch and Innovation Center, Edmund Mach Foundation, San Michele all'Adige, Trento, Italy.
Stefano ToppoComputational Medicine Group (MedComp), Department of Molecular Medicine, University of Padova, Padova, Italy.ORCID 0000-0002-0246-3119

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationDefining 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.

resultsThe 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.

Indexed as

AlgorithmsDatabases, FactualGene OntologyMolecular Sequence Annotation

Identifiers

PMID37672040
PMCPMC10500080

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.