Literature DB >> 30815161

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

Rashmie Abeysinghe1, Xufeng Qu1, Licong Cui1,2.   

Abstract

Non-Lattice Subgraphs (NLSs) are graph fragments of a terminology which violates the lattice property, a desirable property for a well-formed terminology. They have been proven to be useful in identifying inconsistencies in biomed-ical terminologies. Similar NLSs may denote similar inconsistencies that may suggest possibly similar remediations. Therefore, we investigate a structural-semantic-based approach to identify similar NLSs in the Gene Ontology (GO). For an input NLS, we first obtain all its isomorphic NLSs. Then, we compare each concept of the input NLS with the corresponding concept in an isomorphic NLS and then compute a similarity score for the two NLSs. Applying this approach to 10 different structures of NLSs in GO, we found that 38.43% (910/2368) of NLSs have at least one similar NLS. We also observed some interesting lexical patterns frequently existing in similar NLSs. Our approach may be applicable to other biomedical terminologies for identifying similar NLSs.

Mesh:

Year:  2018        PMID: 30815161      PMCID: PMC6371383     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  14 in total

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3.  Biomedical ontologies in action: role in knowledge management, data integration and decision support.

Authors:  O Bodenreider
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Review 4.  A review of auditing methods applied to the content of controlled biomedical terminologies.

Authors:  Xinxin Zhu; Jung-Wei Fan; David M Baorto; Chunhua Weng; James J Cimino
Journal:  J Biomed Inform       Date:  2009-03-12       Impact factor: 6.317

5.  Identifying redundant and missing relations in the gene ontology.

Authors:  Fleur Mougin
Journal:  Stud Health Technol Inform       Date:  2015

6.  A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships.

Authors:  Christopher Ochs; James Geller; Yehoshua Perl; Yan Chen; Ankur Agrawal; James T Case; George Hripcsak
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7.  Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies.

Authors:  Christopher Ochs; James Geller; Yehoshua Perl; Yan Chen; Junchuan Xu; Hua Min; James T Case; Zhi Wei
Journal:  J Am Med Inform Assoc       Date:  2014-10-21       Impact factor: 4.497

8.  Quality assurance of the gene ontology using abstraction networks.

Authors:  Christopher Ochs; Yehoshua Perl; Michael Halper; James Geller; Jane Lomax
Journal:  J Bioinform Comput Biol       Date:  2015-11-24       Impact factor: 1.122

9.  Mining non-lattice subgraphs for detecting missing hierarchical relations and concepts in SNOMED CT.

Authors:  Licong Cui; Wei Zhu; Shiqiang Tao; James T Case; Olivier Bodenreider; Guo-Qiang Zhang
Journal:  J Am Med Inform Assoc       Date:  2017-07-01       Impact factor: 4.497

10.  Ontology quality assurance through analysis of term transformations.

Authors:  Karin Verspoor; Daniel Dvorkin; K Bretonnel Cohen; Lawrence Hunter
Journal:  Bioinformatics       Date:  2009-06-15       Impact factor: 6.937

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  3 in total

1.  Leveraging Non-lattice Subgraphs to Audit Hierarchical Relations in NCI Thesaurus.

Authors:  Rashmie Abeysinghe; Michael A Brooks; Licong Cui
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

2.  Outlier concepts auditing methodology for a large family of biomedical ontologies.

Authors:  Ling Zheng; Hua Min; Yan Chen; Vipina Keloth; James Geller; Yehoshua Perl; George Hripcsak
Journal:  BMC Med Inform Decis Mak       Date:  2020-12-15       Impact factor: 2.796

Review 3.  A review of auditing techniques for the Unified Medical Language System.

Authors:  Ling Zheng; Zhe He; Duo Wei; Vipina Keloth; Jung-Wei Fan; Luke Lindemann; Xinxin Zhu; James J Cimino; Yehoshua Perl
Journal:  J Am Med Inform Assoc       Date:  2020-10-01       Impact factor: 4.497

  3 in total

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