Literature DB >> 22954631

Impact of ontology evolution on functional analyses.

Anika Groß1, Michael Hartung, Kay Prüfer, Janet Kelso, Erhard Rahm.   

Abstract

MOTIVATION: Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes.
RESULTS: Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.

Mesh:

Year:  2012        PMID: 22954631     DOI: 10.1093/bioinformatics/bts498

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

Review 1.  Management of Dynamic Biomedical Terminologies: Current Status and Future Challenges.

Authors:  M Da Silveira; J C Dos Reis; C Pruski
Journal:  Yearb Med Inform       Date:  2015-08-13

2.  Assessing identity, redundancy and confounds in Gene Ontology annotations over time.

Authors:  Jesse Gillis; Paul Pavlidis
Journal:  Bioinformatics       Date:  2013-01-06       Impact factor: 6.937

3.  Pitfalls in the application of gene-set analysis to genetics studies.

Authors:  Adriana Estela Sedeño-Cortés; Paul Pavlidis
Journal:  Trends Genet       Date:  2014-12       Impact factor: 11.639

4.  Monitoring changes in the Gene Ontology and their impact on genomic data analysis.

Authors:  Matthew Jacobson; Adriana Estela Sedeño-Cortés; Paul Pavlidis
Journal:  Gigascience       Date:  2018-08-01       Impact factor: 6.524

5.  Region Evolution eXplorer - A tool for discovering evolution trends in ontology regions.

Authors:  Victor Christen; Michael Hartung; Anika Groß
Journal:  J Biomed Semantics       Date:  2015-06-01

6.  NoGOA: predicting noisy GO annotations using evidences and sparse representation.

Authors:  Guoxian Yu; Chang Lu; Jun Wang
Journal:  BMC Bioinformatics       Date:  2017-07-21       Impact factor: 3.169

7.  A task-based approach for Gene Ontology evaluation.

Authors:  Erik L Clarke; Salvatore Loguercio; Benjamin M Good; Andrew I Su
Journal:  J Biomed Semantics       Date:  2013-04-15

8.  Mining Relation Reversals in the Evolution of SNOMED CT Using MapReduce.

Authors:  Shiqiang Tao; Licong Cui; Wei Zhu; Mengmeng Sun; Olivier Bodenreider; Guo-Qiang Zhang
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2015-03-23

9.  Measuring the evolution of ontology complexity: the gene ontology case study.

Authors:  Olivier Dameron; Charles Bettembourg; Nolwenn Le Meur
Journal:  PLoS One       Date:  2013-10-11       Impact factor: 3.240

10.  Understanding how and why the Gene Ontology and its annotations evolve: the GO within UniProt.

Authors:  Rachael P Huntley; Tony Sawford; Maria J Martin; Claire O'Donovan
Journal:  Gigascience       Date:  2014-03-18       Impact factor: 6.524

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