NDLI: GOseek: A gene ontology search engine using enhanced keywords

Content Provider	IEEE Xplore Digital Library
Author	Taha, K.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Khalifa Univ. of Sci., Abu Dhabi, United Arab Emirates (Taha, K.)
Abstract	We propose in this paper a biological search engine called GOseek, which overcomes the limitation of current gene similarity tools. Given a set of genes, GOseek returns the most significant genes that are semantically related to the given genes. These returned genes are usually annotated to one of the Lowest Common Ancestors (LCA) of the Gene Ontology (GO) terms annotating the given genes. Most genes have several annotation GO terms. Therefore, there may be more than one LCA for the GO terms annotating the given genes. The LCA annotating the genes that are most semantically related to the given gene is the one that receives the most aggregate semantic contribution from the GO terms annotating the given genes. To identify this LCA, GOseek quantifies the contribution of the GO terms annotating the given genes to the semantics of their LCAs. That is, it encodes the semantic contribution into a numeric format. GOseek uses microarray experiment data to rank result genes based on their significance. We evaluated GOseek experimentally and compared it with a comparable gene prediction tool. Results showed marked improvement over the tool.
Starting Page	1502
Ending Page	1505
File Size	644183
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6609797
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Semantics Databases Ontologies Bioinformatics Genomics Search engines Biological information theory
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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