Evidence map›Paper›PMID 35380657›Full record

ArticleGenetics2022

MOET: a web-based gene set enrichment tool at the Rat Genome Database for multiontology and multispecies analyses.

Mahima Vedi, Harika S Nalabolu, Chien-Wei Lin, Matthew J Hoffman, Jennifer R Smith, Kent Brodie, Jeffrey L De Pons, Wendy M Demos, Adam C Gibson, G Thomas Hayman and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  4. Article
  5. Review
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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

22 authors.

Mahima VediDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-5361-6739
Harika S NalaboluDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-1289-9979
Chien-Wei LinDivision of Biostatistics, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0003-4023-7339
Matthew J HoffmanDepartment of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Jennifer R SmithDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-6443-9376
Kent BrodieClinical and Translational Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-9984-3619
Jeffrey L De PonsDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-7783-1556
Wendy M DemosDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-8037-076X
Adam C GibsonDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-8301-6590
G Thomas HaymanDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-9553-7227
Morgan L HillDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-5488-3927
Mary L KaldunskiDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0003-3645-6803
Logan LamersDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-9013-7155
Stanley J F LaulederkindDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-5356-4174
Ketaki ThoratDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-8288-6671
Jyothi ThotaDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0003-4482-7627
Monika TutajDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-0378-4002
Marek A TutajDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-1025-101X
Shur-Jen WangDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0001-5256-8683
Stacy ZacherInformation Services, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0003-2524-3829
Melinda R DwinellDepartment of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0002-9528-3618
Anne E KwitekDepartment of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA.ORCID 0000-0003-1024-4116

Funding

RAT GENOME DATABASER01HL064541 · NHLBI · MEDICAL COLLEGE OF WISCONSIN · PI ANNE E. KWITEK · 1999 to 2026
$50.0M
Text mining in the CloudU24HG010859 · NHGRI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI CAROL J BULT, PAUL Warren STERNBERG · 2019 to 2026
$42.0M
National Heart, Lung, and Blood Institute (NHLBI) R01LH064541National Human Genome Research Institute (NHGRI) as founding members of the Alliance of Genome Resources U24HG010859NHGRI NIH HHS U24 HG010859NHLBI NIH HHS R01 HL064541
6 · The paper itself

Abstract

Biological interpretation of a large amount of gene or protein data is complex. Ontology analysis tools are imperative in finding functional similarities through overrepresentation or enrichment of terms associated with the input gene or protein lists. However, most tools are limited by their ability to do ontology-specific and species-limited analyses. Furthermore, some enrichment tools are not updated frequently with recent information from databases, thus giving users inaccurate, outdated or uninformative data. Here, we present MOET or the Multi-Ontology Enrichment Tool (v.1 released in April 2019 and v.2 released in May 2021), an ontology analysis tool leveraging data that the Rat Genome Database (RGD) integrated from in-house expert curation and external databases including the National Center for Biotechnology Information (NCBI), Mouse Genome Informatics (MGI), The Kyoto Encyclopedia of Genes and Genomes (KEGG), The Gene Ontology Resource, UniProt-GOA, and others. Given a gene or protein list, MOET analysis identifies significantly overrepresented ontology terms using a hypergeometric test and provides nominal and Bonferroni corrected P-values and odds ratios for the overrepresented terms. The results are shown as a downloadable list of terms with and without Bonferroni correction, and a graph of the P-values and number of annotated genes for each term in the list. MOET can be accessed freely from https://rgd.mcw.edu/rgdweb/enrichment/start.html.

Indexed as

Databases, GeneticGenomeAnimalsGene OntologyInternetMiceRatsSoftwaregene set enrichmentmodel organism databasemultiple ontologymultiple species analysisontologyratweb tool

Identifiers

PMID35380657
PMCPMC8982048

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.