Using Annotations from Controlled Vocabularies to Find Meaningful Associations

Woei-Jyh Lee; Louiqa Raschid; Padmini Srinivasan; Nigam Shah; Daniel Rubin; Natasha Noy

doi:10.1007/978-3-540-73255-6_20

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Book chapter

Using Annotations from Controlled Vocabularies to Find Meaningful Associations

Woei-Jyh Lee, Louiqa Raschid, Padmini Srinivasan, Nigam Shah, Daniel Rubin and Natasha Noy

Data Integration in the Life Sciences, pp.247-263

Lecture Notes in Computer Science, Springer Berlin Heidelberg

2007

DOI: 10.1007/978-3-540-73255-6_20

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Abstract

This paper presents the LSLink (or Life Science Link) methodology that provides users with a set of tools to explore the rich Web of interconnected and annotated objects in multiple repositories, and to identify meaningful associations. Consider a physical link between objects in two repositories, where each of the objects is annotated with controlled vocabulary (CV) terms from two ontologies. Using a set of LSLink instances generated from a background dataset of knowledge we identify associations between pairs of CV terms that are potentially significant and may lead to new knowledge. We develop an approach based on the logarithm of the odds (LOD) to determine a confidence and support in the associations between pairs of CV terms. Using a case study of Entrez Gene objects annotated with GO terms linked to PubMed objects annotated with MeSH terms, we describe a user validation and analysis task to explore potentially significant associations.

associations

LOD

controlled vocabularies

links between data objects

life science link

annotations

confidence and support scores

Details

Title: Subtitle: Using Annotations from Controlled Vocabularies to Find Meaningful Associations
Creators: Woei-Jyh Lee - University of Maryland, College Park, MD 20742, USA
Louiqa Raschid - University of Maryland, College Park, MD 20742, USA
Padmini Srinivasan - The University of Iowa, Iowa City, IA 52242, USA
Nigam Shah - Stanford University, Stanford, CA 94305, USA
Daniel Rubin - Stanford University, Stanford, CA 94305, USA
Natasha Noy - Stanford University, Stanford, CA 94305, USA
Resource Type: Book chapter
Publication Details: Data Integration in the Life Sciences, pp.247-263
Publisher: Springer Berlin Heidelberg; Berlin, Heidelberg
Series: Lecture Notes in Computer Science
DOI: 10.1007/978-3-540-73255-6_20
eISSN: 1611-3349
ISSN: 0302-9743
Language: English
Date published: 2007
Academic Unit: Nursing; Business Analytics; Computer Science
Record Identifier: 9984003014002771

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