• Home
  • Browse
    • Current Issue
    • By Issue
    • By Author
    • By Subject
    • Author Index
    • Keyword Index
  • Journal Info
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Editorial Staff
    • Publication Ethics
    • Indexing and Abstracting
    • Related Links
    • FAQ
    • Peer Review Process
    • News
  • Guide for Authors
  • Submit Manuscript
  • Reviewers
  • Contact Us
 
  • Login
  • Register
Home Articles List Article Information
  • Save Records
  • |
  • Printable Version
  • |
  • Recommend
  • |
  • How to cite Export to
    RIS EndNote BibTeX APA MLA Harvard Vancouver
  • |
  • Share Share
    CiteULike Mendeley Facebook Google LinkedIn Twitter
Asian Pacific Journal of Cancer Prevention
arrow Articles in Press
arrow Current Issue
Journal Archive
Volume Volume 20 (2019)
Volume Volume 19 (2018)
Issue Issue 12
Issue Issue 11
Issue Issue 10
Issue Issue 9
Issue Issue 8
Issue Issue 7
Issue Issue 6
Issue Issue 5
Issue S1
Issue Issue 4
Issue Issue 3
Issue Issue 2
Issue Issue 1
Volume Volume 18 (2017)
Volume Volume 17 (2016)
Volume Volume 16 (2015)
Volume Volume 15 (2014)
Volume Volume 14 (2013)
Volume Volume 13 (2012)
Volume Volume 12 (2011)
Volume Volume 11 (2010)
Volume Volume 10 (2009)
Volume Volume 9 (2008)
Volume Volume 8 (2007)
Volume Volume 7 (2006)
Volume Volume 6 (2005)
Volume Volume 5 (2004)
Volume Volume 4 (2003)
Volume Volume 3 (2002)
Volume Volume 2 (2001)
Volume Volume 1 (2000)
Maran, P., R, T. (2018). Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework. Asian Pacific Journal of Cancer Prevention, 19(2), 561-564. doi: 10.22034/APJCP.2018.19.2.561
Pyingkodi Maran; Thangarajan R. "Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework". Asian Pacific Journal of Cancer Prevention, 19, 2, 2018, 561-564. doi: 10.22034/APJCP.2018.19.2.561
Maran, P., R, T. (2018). 'Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework', Asian Pacific Journal of Cancer Prevention, 19(2), pp. 561-564. doi: 10.22034/APJCP.2018.19.2.561
Maran, P., R, T. Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework. Asian Pacific Journal of Cancer Prevention, 2018; 19(2): 561-564. doi: 10.22034/APJCP.2018.19.2.561

Informative Gene Selection for Cancer Classification with Microarray Data Using a Metaheuristic Framework

Article 40, Volume 19, Issue 2, February 2018, Page 561-564  XML PDF (296.64 K)
Document Type: Research Articles
DOI: 10.22034/APJCP.2018.19.2.561
Authors
Pyingkodi Maran email 1; Thangarajan R2
1Department of Computer Applications, Kongu Engineering College Erode, TamilNadu, India.
2Department of Computer Science and Engineering, Kongu Engineering College Erode, TamilNadu, India.
Receive Date: 03 November 2017,  Revise Date: 16 November 2017,  Accept Date: 09 January 2018 
Abstract
Objective: Cancer diagnosis is one of the most vital emerging clinical applications of microarray data. Due to
the high dimensionality, gene selection is an important step for improving expression data classification performance.
There is therefore a need for effective methods to select informative genes for prediction and diagnosis of cancer.
The main objective of this research was to derive a heuristic approach to select highly informative genes. Methods:
A metaheuristic approach with a Genetic Algorithm with Levy Flight (GA-LV) was applied for classification of cancer
genes in microarrays. The experimental results were analyzed with five major cancer gene expression benchmark datasets.
Result: GA-LV proved superior to GA and statistical approaches, with 100% accuracy for the dataset for Leukemia,
Lung and Lymphoma. For Prostate and Colon datasets the GA-LV was 99.5% and 99.2% accurate, respectively.
Conclusion: The experimental results show that the proposed approach is suitable for effective gene selection with all
benchmark datasets, removing irrelevant and redundant genes to improve classification accuracy.
Keywords
Cancer diagnosis; Gene Treatments; Genomics; Gene Expression data; Genetic algorithm
Main Subjects
Other sciences
Statistics
Article View: 244
PDF Download: 151
Home | Glossary | News | Aims and Scope | Sitemap
Top Top

 



 

Journal Management System. Designed by sinaweb.