Modification of Support Vector Machine for Microarray Data Analysis

Sk Sarif Hassan

Modification of Support Vector Machine for Microarray Data Analysis

Sk Sarif Hassan * § PhD, Assistant Professor in Mathematics

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§ Indian School of Mines ,Dhanbad, India .Institute of...

Modification of Support Vector Machine for Microarray Data Analysis

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Abstract

The role of protuberant data analysis in selection of certain genes having distinctive level of activities between conditions of interest i.e diseased gene and normal genes is very significant. Nowa-days it is become a standard in gene analysis that microarray of DNA is a crucial data preparation step in systemization and other biological analysis. We consider the problem of constructing an accurate prediction rule for separating the different labels of genes in microarray gene expression data. Use of SVM in such data analysis is not new but it is not up to the mark we desire. So in this manuscript, we have tried to modify Support Vector Machine (SVM) for better accuracy in cancer genes systemization. Here we have modified SVM to account for gene redundancy and keep a check on it. In the other approach, instead of keeping bias a constant in SVM, we have tried to modify SVM by bias variation which we call as Orthogonal Vertical Permutator (OVP).

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Sk Sarif Hassan. 2013. "Modification of Support Vector Machine for Microarray Data Analysis". Global Journal of Computer Science and Technology - A: Hardware & Computation GJCST-A Volume 13 (GJCST Volume 13 Issue A1).

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GJCST Volume 13 Issue A1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Microarray orthogonal vertical permutator redundancy support vector machine

Classification

GJCST-A Classification C.1.2

Submission ReceivedDecember 15, 2012
Peer Review Double Blind
Handling Editor
Accepted January 2, 2013
Published January 15, 2013

Version of record

v1.2

Issue date

August 1, 2013

Language

English

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Article Matrices

Total Score: 192

Country: Switzerland

Subject: Global Journal of Computer Science and Technology

Authors: Vrushali Dipak Fangal, Dr. Sk. Sarif Hassan (PhD/Dr. count: 1)

View Count (all-time): 563

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Publish Date: 2013 01, Tue

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Total Views: 3.9K

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