NDLI: Extracting very simple diagnostic rules from microarray data

Content Provider	IEEE Xplore Digital Library
Author	Lipo Wang Feng Chu
Copyright Year	2010
Description	Author affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Lipo Wang; Feng Chu)
Abstract	We present an approach to deriving very simple classification rules from microarray data by first selecting very small gene subsets that can ensure highly accurate classification of cancers. Finding such minimum gene subsets can greatly reduce the computational load and “noise” arising from irrelevant genes. The derived simple classification rules allow for accurate diagnosis without the need for any classifiers. This work can simplify gene expression tests by including only a very small number of genes rather than thousands or tens of thousands of genes, which can significantly bring down the cost for cancer testing. These studies also call for further investigations into possible biological relationship between these small number of genes and cancer development and treatment. For example, we report the following simple, and yet 100% accurate, diagnostic rules involving only 2 genes to separate the 3 types of lymphoma patients: the patient has diffuse large B-cell lymphoma (DLBCL), if and only if the expression level of gene GENE1622X is greater than −0.75; the patient has chronic lymphocytic leukaemia (CLL), if and only if the expression level of gene GENE540X is less than −1; and the patient has follicular lymphoma (FL) otherwise, i.e., if and only if the expression level of gene GENE1622X is less than −0.75 and the expression level of gene GENE540X is greater than −1.
Starting Page	807
Ending Page	810
File Size	251967
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626565
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cancer Accuracy Gene expression Testing Bioinformatics Training data Fuzzy neural networks
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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
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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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