title: Semantic Signature: Comparative Interpretation of Gene Expression on a Semantic Space.
abstract: Background. Interpretation of microarray data remains challenging because biological meaning should be extracted from enormous numeric matrices and be presented explicitly. Moreover, huge public repositories of microarray dataset are ready to be exploited for comparative analysis. This study aimed to provide a platform where essential implication of a microarray experiment could be visually expressed and various microarray datasets could be intuitively compared. Results. On the semantic space, gene sets from Molecular Signature Database (MSigDB) were plotted as landmarks and their relative distances were calculated by Lin's semantic similarity measure. By formal concept analysis, a microarray dataset was transformed into a concept lattice with gene clusters as objects and Gene Ontology terms as attributes. Concepts of a lattice were located on the semantic space reflecting semantic distance from landmarks and edges between concepts were drawn; consequently, a specific geographic pattern could be observed from a microarray dataset. We termed a distinctive geography shared by microarray datasets of the same category as "semantic signature." Conclusions. "Semantic space," a map of biological entities, could serve as a universal platform for comparative microarray analysis. When microarray data were displayed on the semantic space as concept lattices, "semantic signature," characteristic geography for a microarray experiment, could be discovered.
authors.affiliation: Seoul National University Biomedical Informatics (SNUBI), Seoul 110-799, Republic of Korea; LabGenomics Clinical Research Institute, LabGenomics, Seongnam 463-400, Republic of Korea.
authors.forename: Jihun
authors.identifier: 0000-0001-7822-6120
authors.initials: J
authors.lastname: Kim
authors.affiliation: Seoul National University Biomedical Informatics (SNUBI), Seoul 110-799, Republic of Korea; Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul 110-799, Republic of Korea; Departments of Biomedical Engineering, Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.
authors.forename: Keewon
authors.identifier: 0000-0001-6597-578X
authors.initials: K
authors.lastname: Kim
authors.affiliation: Seoul National University Biomedical Informatics (SNUBI), Seoul 110-799, Republic of Korea; Systems Biomedical Informatics Research Center, Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.
authors.forename: Ju Han
authors.identifier: 0000-0003-1522-9038
authors.initials: JH
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D000818:Animals; D016208:Databases, Factual; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D005843:Geography; D008099:Liver / Q000187:drug effects; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D012660:Semantics