Hierarchical Text Categorization as a Tool of Associating Genes with Gene Ontology Codes

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TypeArticle
ConferenceSecond European Workshop on Data Mining and Text Mining forBioinformatics held in conjunction with Fifteenth European Conference on Machine Learning (ECML) and the Eighth European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), September 24, 2004., Pisa, Italy
AbstractA great deal of genomics information accumulated through years is available nowadays in on-line text repositories such as Medline. These resources are essential for biomedical researchers in their everyday activities on planning and performing experiments and verifying the results. However, these resources do not still provide adequate mechanisms for retrieving the requisite information. We propose a new tool for assisting biologists with literature search for the task of associating genes with Gene Ontology codes. Unlike previous research, we design the hierarchical text categorization framework to address this problem. The hierarchical approach helps visualize the results, address the scalability issue, improve classification accuracy and trade off between precision and recall.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48050
NPARC number5765106
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Record identifiercb804a55-f460-49d1-a1db-4a34e423da07
Record created2009-03-29
Record modified2016-05-09
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