Literature DB >> 25991129

Identifying redundant and missing relations in the gene ontology.

Fleur Mougin1.   

Abstract

Significant efforts have been undertaken for providing the Gene Ontology (GO) in a computable format as well as for enriching it with logical definitions. Automated approaches can thus be applied to GO for assisting its maintenance and for checking its internal coherence. However, inconsistencies may still remain within GO. In this frame, the objective of this work was to audit GO relationships. First, reasoning over relationships was exploited for detecting redundant relations existing between GO concepts. Missing necessary and sufficient conditions were then identified based on the compositional structure of the preferred names of GO concepts. More than one thousand redundant relations and 500 missing necessary and sufficient conditions were found. The proposed approach was thus successful for detecting inconsistencies within GO relations. The application of lexical approaches as well as the exploitation of synonyms and textual definitions could be useful for identifying additional necessary and sufficient conditions. Multiple necessary and sufficient conditions for a given GO concept may be indicative of inconsistencies.

Mesh:

Year:  2015        PMID: 25991129

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  5 in total

1.  Identifying Similar Non-Lattice Subgraphs in Gene Ontology based on Structural Isomorphism and Semantic Similarity of Concept Labels.

Authors:  Rashmie Abeysinghe; Xufeng Qu; Licong Cui
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

Review 2.  Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

Authors:  Muhammad Amith; Zhe He; Jiang Bian; Juan Antonio Lossio-Ventura; Cui Tao
Journal:  J Biomed Inform       Date:  2018-02-17       Impact factor: 6.317

3.  A Comparison of Exhaustive and Non-lattice-based Methods for Auditing Hierarchical Relations in Gene Ontology.

Authors:  Rashmie Abeysinghe; Fengbo Zheng; Licong Cui
Journal:  AMIA Annu Symp Proc       Date:  2022-02-21

4.  FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies.

Authors:  Guangming Xing; Guo-Qiang Zhang; Licong Cui
Journal:  BioData Min       Date:  2016-10-10       Impact factor: 2.522

5.  SSIF: Subsumption-based Sub-term Inference Framework to audit Gene Ontology.

Authors:  Rashmie Abeysinghe; Eugene W Hinderer; Hunter N B Moseley; Licong Cui
Journal:  Bioinformatics       Date:  2020-05-01       Impact factor: 6.937

  5 in total

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