Evidence map›Paper›PMID 35164667›Full record

ArticleBMC bioinformatics2022

MonaGO: a novel gene ontology enrichment analysis visualisation system.

Ziyin Xin, Yujun Cai, Louis T Dang, Hannah M S Burke, Jerico Revote, Natalie Charitakis, Denis Bienroth, Hieu T Nim, Yuan-Fang Li, Mirana Ramialison

Abstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  4. Aberrant Mitochondrial Metabolism in Alzheimer's Disease Links Energy Stress with Ferroptosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
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  7. Development of a Sexological Ontology.Sensors (Basel, Switzerland) · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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  17. A53T mutant α-synuclein fibrils formed in macrophage are spread to neurons.Cellular and molecular life sciences : CMLS · 2022
    Article
  18. Article
  19. 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

10 authors.

Ziyin Xin *Faculty of IT, Monash University, Clayton, VIC, Australia.
Yujun Cai *Faculty of IT, Monash University, Clayton, VIC, Australia.
Louis T DangAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Hannah M S BurkeAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Jerico RevoteMonash eResearch Centre, Monash University, Melbourne, VIC, Australia.
Natalie CharitakisMurdoch Children's Research Institute, Parkville, VIC, Australia.
Denis BienrothMurdoch Children's Research Institute, Parkville, VIC, Australia.
Hieu T NimFaculty of IT, Monash University, Clayton, VIC, Australia. hieu.nim@monash.edu.
Yuan-Fang LiFaculty of IT, Monash University, Clayton, VIC, Australia. yuanfang.li@monash.edu.
Mirana RamialisonAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia. mirana.ramialison@monash.edu.ORCID http://orcid.org/0000-0001-6315-4777

Funding

Australian Research Council Discovery ProjectNational Health and Medical Research Council Career Development Fellowship
6 · The paper itself

Abstract

backgroundGene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking.

resultsMonash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options.

conclusionMonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.

Indexed as

SoftwareCluster AnalysisGene OntologyProbabilityReproducibility of ResultsGene ontologyGO enrichmentInteractive visualisationSemantic webWeb services

Identifiers

PMID35164667
PMCPMC8845231

What OpenQuestion holds

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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.