InterOnto - Ranking Inter-Ontology Links

Entries in biomolecular databases are often annotated with concepts from different ontologies and thereby establish links between pairs of concepts. Such links may reveal meaningful relationships between linked concepts, however they could as well relate concepts by chance. In this work we present InterOnto, a methodology that allows us to rank concept pairs to identify the most meaningful associations. The novelty of our approach compared to previous works is that we take the entire structure of the involved ontologies into account. This way, our method even finds links that are not present in the annotated data, but may be inferred through subsumed concept pairs. We have evaluated our methodology both quantitatively and qualitatively. Using real-life data from TAIR we show that our proposed scoring function is able to identify the most representative concept pairs while preventing overgeneralization. In comparison to prior work our method generally yields rankings of equivalent or better quality.

[1]  Patrick Lambrix,et al.  Alignment of Biomedical Ontologies Using Life Science Literature , 2006, KDLL.

[2]  L. Stein,et al.  Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages , 2005, Comparative and functional genomics.

[3]  Eric G. Bremer.  Knowledge Discovery in Life Science Literature, PAKDD 2006 International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings , 2006, KDLL.

[4]  Louiqa Raschid,et al.  Using Annotations from Controlled Vocabularies to Find Meaningful Associations , 2007, DILS.

[5]  Torulf Mollestad,et al.  Additional Gene Ontology structure for improved biological reasoning , 2006, Bioinform..

[6]  Philip Resnik,et al.  Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[7]  Steffen Staab,et al.  Measuring Similarity between Ontologies , 2002, EKAW.

[8]  Yannis Kalfoglou,et al.  Ontology mapping: the state of the art , 2003, The Knowledge Engineering Review.

[9]  Louiqa Raschid,et al.  Exploiting Ontology Structure and Patterns of Annotation to Mine Significant Associations between Pairs of Controlled Vocabulary Terms , 2008, DILS.

[10]  Myoung-Ho Kim,et al.  Ranking Documents in Thesaurus-Based Boolean Retrieval Systems , 1994, Inf. Process. Manag..

[11]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[12]  Emilly Budlong.  Multimedia Information Extraction , 2007 .

[13]  Olivier Bodenreider,et al.  Non-Lexical Approaches to Identifying Associative Relations in the Gene Ontology , 2004, Pacific Symposium on Biocomputing.

[14]  Yuji Kamiya,et al.  PHYTOCHROME REGULATION OF GIBBERELLIN 3β-HYDROXYLASE GENES IN GERMINATING ARABIDOPSIS SEEDS , 1999 .

[15]  Mark A. Musen,et al.  The PROMPT suite: interactive tools for ontology merging and mapping , 2003, Int. J. Hum. Comput. Stud..

[16]  Felix Naumann,et al.  Graph-based concept identification and disambiguation for enterprise search , 2010, WWW '10.

[17]  David W. Conrath,et al.  Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy , 1997, ROCLING/IJCLCLP.

[18]  Andreas Thor,et al.  Instance-Based Matching of Large Life Science Ontologies , 2007, DILS.

[19]  Silvana Castano,et al.  Ontology and Instance Matching , 2011, Knowledge-Driven Multimedia Information Extraction and Ontology Evolution.

[20]  Georgios Paliouras,et al.  Knowledge-Driven Multimedia Information Extraction and Ontology Evolution - Bridging the Semantic Gap , 2011, Knowledge-Driven Multimedia Information Extraction and Ontology Evolution.

[21]  Ian Horrocks,et al.  Ontologies and the semantic web , 2008, CACM.

[22]  Samir Khuller,et al.  Dense Subgraphs with Restrictions and Applications to Gene Annotation Graphs , 2010, RECOMB.

[23]  Tanya Z. Berardini,et al.  The Arabidopsis Information Resource (TAIR): gene structure and function annotation , 2007, Nucleic Acids Res..

[24]  Stefan Schlobach,et al.  An Empirical Study of Instance-Based Ontology Matching , 2007, ISWC/ASWC.

[25]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[26]  Brad T. Sherman,et al.  Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists , 2008, Nucleic acids research.