Evidence map›Paper›PMID 32875947›Full record

ArticleOpen biology2020

Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns.

Valerie Wood, Seth Carbon, Midori A Harris, Antonia Lock, Stacia R Engel, David P Hill, Kimberly Van Auken, Helen Attrill, Marc Feuermann, Pascale Gaudet and 4 more

Open access · goldAbstract read
In one paragraph

Article in Open biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. A roadmap for the functional annotation of protein families: a community perspective.Database : the journal of biological databases and curation · 2022
    Article
  5. Article
  6. Article
  7. 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

14 authors at 7 institutions in 3 countries.

Valerie WoodCambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK.
Seth CarbonDivision of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Midori A HarrisCambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK.
Antonia LockDepartment of Genetics, Evolution and Environment, University College London, London WC1E 6B, UK.
Stacia R EngelDepartment of Genetics, Stanford University, Palo Alto, CA 94304-5477, USA.
David P HillMouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA.
Kimberly Van AukenDivision of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125, USA.
Helen AttrillDepartment of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK.
Marc FeuermannSwiss Institute of Bioinformatics, 1 Michel-Servet, 1204 Geneva, Switzerland.
Pascale GaudetSwiss Institute of Bioinformatics, 1 Michel-Servet, 1204 Geneva, Switzerland.
Ruth C LoveringFunctional Gene Annotation, Preclinical and Fundamental Science, Institute of Cardiovascular Science, University College London, London WC1E 6JF, UK.
Sylvain PouxSwiss Institute of Bioinformatics, 1 Michel-Servet, 1204 Geneva, Switzerland.
Kim M RutherfordCambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK.
Christopher J MungallDivision of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
University of Cambridge · GBSIB Swiss Institute of Bioinformatics · CHLawrence Berkeley National Laboratory · USUniversity College London · GBCalifornia Institute of Technology · USJackson Laboratory · USPalo Alto University · US

Funding

Text mining in the CloudU24HG010859 · NHGRI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI CAROL J BULT, PAUL Warren STERNBERG · 2019 to 2026
$42.0M
Resource ProjectU41HG002273 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHERRY, J. MICHAEL, MUNGALL, CHRISTOPHER J · 2012 to 2021
$34.7M
Resource Project CoreU41HG000739 · NHGRI · HARVARD UNIVERSITY · PI PERRIMON, NORBERT · 2014 to 2022
$32.3M
Genomic Resource for the Yeast SaccharomycesU41HG001315 · NHGRI · STANFORD UNIVERSITY · PI CHERRY, J. MICHAEL · 2011 to 2020
$26.4M
WormBase: a core data resource for C. elegans and other nematodesU24HG002223 · NHGRI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI TIM SCHEDL, PAUL Warren STERNBERG · 2018 to 2026
$18.9M
Genomic Resource for the Yeast SaccharomycesU24HG001315 · NHGRI · STANFORD UNIVERSITY · PI Stacia Engel, Gavin J Sherlock · 2021 to 2026
$10.9M
Biotechnology and Biological Sciences Research Council BB/P024602/1Medical Research Council MR/N030117/1Medical Research Council MR/S000453/1NHGRI NIH HHS U24 HG001315NHGRI NIH HHS U24 HG002223NHGRI NIH HHS U24 HG010859NHGRI NIH HHS U41 HG000739NHGRI NIH HHS U41 HG001315NHGRI NIH HHS U41 HG002273Wellcome Trust
6 · The paper itself

Abstract

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

Indexed as

Gene OntologyMolecular Sequence AnnotationComputational BiologyDatabases, GeneticEvolution, MolecularGenome, FungalGenomicsQuality ControlSchizosaccharomycesWeb BrowserWorkflowannotationbiocurationgene ontologyquality control

Identifiers

PMID32875947
PMCPMC7536087
OpenAlexW3082808899

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.