NDLI: Metasample-Based Sparse Representation for Tumor Classification

Content Provider	ACM Digital Library
Author	Zheng, Chun-Hou Shiu, Chi Keung Ng, To-Yee Huang, De-Shuang Zhang, Lei
Abstract	A reliable and accurate identification of the type of tumors is crucial to the proper treatment of cancers. In recent years, it has been shown that sparse representation (SR) by l_1-norm minimization is robust to noise, outliers and even incomplete measurements, and SR has been successfully used for classification. This paper presents a new SR-based method for tumor classification using gene expression data. A set of metasamples are extracted from the training samples, and then an input testing sample is represented as the linear combination of these metasamples by l_1-regularized least square method. Classification is achieved by using a discriminating function defined on the representation coefficients. Since l_1-norm minimization leads to a sparse solution, the proposed method is called metasample-based SR classification (MSRC). Extensive experiments on publicly available gene expression data sets show that MSRC is efficient for tumor classification, achieving higher accuracy than many existing representative schemes.
Starting Page	1273
Ending Page	1282
Page Count	10
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2011.20
Volume Number	8
Issue Number	5
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-09-01
Access Restriction	Subscribed
Subject Keyword	Tumors classification, sparse representation, metasample, gene expression data.
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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