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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Huiru Zheng Azuaje, F. Haiying Wang |
| Copyright Year | 2010 |
| Description | Author affiliation: School of Computing and, Mathematics, Computer Science, Research Institute, University of Ulster, Co. Antrim, UK (Huiru Zheng; Haiying Wang) || Laboratory of Cardiovascular, Research, Public Research Centre for Health, (CRP-Santé), L-1150, Luxembourg (Azuaje, F.) |
| Abstract | In recent years there has been a growing trend towards the adoption of ontologies to support comprehensive, large-scale functional genomics research. This paper introduces seGOsa, a user-friendly cross-platform system to support large-scale assessment of Gene Ontology (GO)-driven similarity among gene products. Using information-theoretic approaches, the system exploits both topological features of the GO (i.e., between-term relationships in the hierarchy) and statistical features of the model organism databases annotated to the GO (i.e., term frequency) to assess functional similarity among gene products. Based on the assumption that the more information two terms share in common, the more similar they are, three GO-driven similarity measures (Resnik's, Lin's and Jiang's metrics) have been implemented to measure between-term similarity within each of the GO hierarchies. Meanwhile, seGOsa offers two approaches (simple and highest average similarity) to assessing the similarity between gene products based on the aggregation of between-term similarities. The program is freely available for non-profit use on request from the authors. |
| Starting Page | 539 |
| Ending Page | 542 |
| File Size | 521085 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424483068 |
| e-ISBN | 9781424483075 |
| DOI | 10.1109/BIBM.2010.5706624 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Databases information content Semantics Genomics Ontologies Semantic similarity Gene expression Bioinformatics Gene Ontology |
| Content Type | Text |
| Resource Type | Article |
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