NDLI: Ontology-based functional classification of genes: Evaluation with reference sets and overlap analysis

Content Provider	IEEE Xplore Digital Library
Author	Benabderrahmane, S. Devignes, M.D. Tabbone, M.S. Napoli, A. Poch, O.
Copyright Year	2011
Description	Author affiliation: LORIA UMR7503 (CNRS, INRIA, Nancy-Université), Équipe Orpailleur, Bâtiment B, Campus scientifique, BP239, 54506, Vandoeuvre-lès-Nancy Cedex, France (Benabderrahmane, S.; Devignes, M.D.; Tabbone, M.S.; Napoli, A.) \|\| L.B.G.I., CNRS UMR7104, IGBMC, 1 rue Laurent Fries, 67404, Illkirch Strasbourg, France (Poch, O.)
Abstract	Functional classification involves grouping genes according to their molecular functions or the biological processes they participate in. This unsupervised classification task is essential for interpreting gene datasets produced by post-genomic experiments. As the functional annotation of genes is mostly based on the Gene Ontology (GO), many similarity measures using the GO have been described, but few of them have been used for clustering. In this paper we evaluate functional classification of genes using our previously described IntelliGO semantic similarity measure with the help of reference sets. These sets consist of genes taken from human and yeast KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways and Pfam clans. Hierarchical clustering and heatmap visualization are used to illustrate the advantages of IntelliGO over several other measures. Because genes often belong to more than one reference set, the fuzzy C-means clustering algorithm is then applied to the datasets using IntelliGO. The F-score method is used to estimate the quality of clustering and the optimal number of clusters. The results are compared with those obtained from the state-of-the-art DAVID (Database for Annotation Visualization and Integrated Discovery) functional classification method. Overlap analysis allows to study the matching between clusters and reference sets, and leads us to propose a set-difference method for discovering missing information. The IntelliGO similarity measure, the clustering tool and the reference sets used for evaluation are available at: http://plateforme-mbi.loria.fr/intelligo
Starting Page	201
Ending Page	208
File Size	1071416
Page Count	8
File Format	PDF
ISBN	9781457716126
e-ISBN	9781457716133
DOI	10.1109/BIBMW.2011.6112375
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Visualization overlap analysis Databases Heating Semantics Clustering algorithms Humans gene functional classification fuzzy clustering Semantic similarity measure Gene Ontology
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
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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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