NDLI: LevenshteinOWA operators for gene product similarity, clustering, and knowledge discovery

Content Provider	IEEE Xplore Digital Library
Author	Keller, J.M. Bezdek, J.C. Popescu, M. Pal, N. Mitchell, J.A. Huband, J.
Copyright Year	2005
Description	Author affiliation: Electr. & Comput. Eng. Dept., Univ. of Missouri-Columbia, Columbia, MO, USA (Keller, J.M.)
Abstract	The human genome project and its related research bring the promise of a revolution in our knowledge of the function of genes and their interactions with environmental factors across multiple species. However, there is a huge amount of information related to these genes that is located in multiple knowledge sources available on the Internet, with much of the data changing rapidly. High density microarray technologies and newer proteomics techniques allow for the analyses of thousands of genes. In clustering and subsequent knowledge discovery on unknown gene products, the primary features to date are the gene sequence and expression values found following a microarray experiment. One major goal is to determine the function of this gene product and its similarity in function or structure to other up-regulated or down-regulated gene products. Many measures have been proposed to calculate closeness of sequences. However, for many gene products, additional information comes from the set of gene ontology (GO) annotations and the set of journal abstracts related to the gene product. For these genes, it is reasonable to include similarity measures based on the terms found in the GO and/or the index term sets of the related documents (MeSH annotations). In both cases we deal with comparing two sets of terms coming from a taxonomy (GO or MeSH.). In this talk we propose ordered weighted average (OWA) measures for computing the similarity of two sets of terms found in a taxonomy (and hence, the two gene products annotated with terms from the taxonomy). The operators we identify are also known as linear combinations of order statistics (LOS), special cases of the Choquet integral, and qualify as OWA operators because the weights are defined by linguistic quantifiers. Using them, we build similarity measures based on the collection of pairwise term "associations" found using an information theoretic approach. The advantage of the OWA operators is the fact that they are simply built out of pairwise coefficients of association and the measures for the integral fusion can be tailored to produce "linguistic" combinations, e.g., "at least two terms must support the connection". We present examples and comparisons and show the use of our GO approach for knowledge discovery, annotation verification, visualization and clustering.
Starting Page	233
Ending Page	234
File Size	286297
Page Count	2
File Format	PDF
ISBN	078039187X
DOI	10.1109/NAFIPS.2005.1548539
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Taxonomy Open wireless architecture Humans Genomics Bioinformatics Environmental factors Internet Proteomics Ontologies Abstracts
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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