Skip Navigation



Briefings in Bioinformatics Advance Access published online on June 18, 2008
Briefings in Bioinformatics, doi:10.1093/bib/bbn027
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
9/5/392    most recent
bbn027v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Ma, S.
Right arrow Articles by Huang, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ma, S.
Right arrow Articles by Huang, J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2008. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

Penalized feature selection and classification in bioinformatics

Shuangge Ma and Jian Huang

Corresponding author. Shuangge Ma, 60 College ST, LEPH 209, New Haven CT, 06510, USA. Tel: 203-785-3119; Fax: 203-785-6912; E-mail: shuangge.ma{at}yale.edu

In bioinformatics studies, supervised classification with high-dimensional input variables is frequently encountered. Examples routinely arise in genomic, epigenetic and proteomic studies. Feature selection can be employed along with classifier construction to avoid over-fitting, to generate more reliable classifier and to provide more insights into the underlying causal relationships. In this article, we provide a review of several recently developed penalized feature selection and classification techniques—which belong to the family of embedded feature selection methods—for bioinformatics studies with high-dimensional input. Classification objective functions, penalty functions and computational algorithms are discussed. Our goal is to make interested researchers aware of these feature selection and classification methods that are applicable to high-dimensional bioinformatics data.

Keywords: bioinformatics application, feature selection, penalization

Submitted: February 12, 2008. Accepted: May 20, 2008.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Brief BioinformHome page
B. Duval and J.-K. Hao
Advances in metaheuristics for gene selection and classification of microarray data
Brief Bioinform, September 29, 2009; (2009) bbp035v1.
[Abstract] [Full Text] [PDF]

Home page
 Brief BioinformHome page
L. J. Lancashire, C. Lemetre, and G. R. Ball
An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies
Brief Bioinform, May 1, 2009; 10(3): 315 - 329.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.