NDLI: A Knowledge Driven Regression Model for Gene Expression and Microarray Analysis

Content Provider	IEEE Xplore Digital Library
Author	Rong Jin Luo Si Srivastava, S. Zheng Li Chan, C.
Copyright Year	2006
Description	Author affiliation: Fac. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI (Rong Jin)
Abstract	The linear regression model has been widely used in the analysis of gene expression and microarray data to identify a subset of genes that are important to a given metabolic function. One of the key challenges in applying the linear regression model to gene expression data analysis arises from the sparse data problem, in which the number of genes is significantly larger than the number of conditions. To resolve this problem, we present a knowledge driven regression model that incorporates the knowledge of genes from the Gene Ontology (GO) database into the linear regression model. It is based on the assumption that two genes are likely to be assigned similar weights when they share similar sets of GO codes. Empirical studies show that the proposed knowledge driven regression model is effective in reducing the regression errors, and furthermore effective in identifying genes that are relevant to a given metabolite
Sponsorship	IEEE EMB
Starting Page	5326
Ending Page	5329
File Size	148124
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.260347
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gene expression Linear regression Independent component analysis Databases Data analysis Ontologies Biological system modeling Cities and towns USA Councils Biological processes
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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
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