ScienceDirect® Home Skip Main Navigation Links
You have guest access to ScienceDirect. Find out more.
 
Home
Browse
My Settings
Alerts
Help
 Quick Search
 Search tips (Opens new window)
    Clear all fields    
advertisementadvertisement
Computational Biology and Chemistry
Volume 30, Issue 3, June 2006, Pages 169-178
 
Font Size: Decrease Font Size  Increase Font Size
 Abstract - selected
Article
Purchase PDF (769 K)

  E-mail Article   
  Add to my Quick Links   
Bookmark and share in 2collab (opens in new window)
Request permission to reuse this article
  Cited By in Scopus (0)
 
 
 
Related Articles in ScienceDirect
View More Related Articles
 
View Record in Scopus
 
doi:10.1016/j.compbiolchem.2006.02.003    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2006 Elsevier Ltd All rights reserved.

Selecting effective siRNA sequences based on the self-organizing map and statistical techniques

Shigeru TakasakiCorresponding Author Contact Information, a, E-mail The Corresponding Author, Yoshihiro Kawamuraa and Akihiko Konagayaa

aRIKEN Genomic Sciences Center (GSC), Suehiro-cho 1-7-22-E216, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan

Received 11 January 2006; 
accepted 28 February 2006. 
Available online 5 April 2006.

Purchase the full-text article



References and further reading may be available for this article. To view references and further reading you must purchase this article.

Abstract

Short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells but varies markedly in its gene-silencing efficacy. Although many design rules/guidelines for effective siRNAs based on various criteria have been reported recently, there are only a few consistencies among them. This makes it difficult to select effective siRNA sequences in mammalian genes. Here, we propose a new method for selecting effective siRNA target sequences on the basis of the self-organizing map (SOM) technique and statistical significance analyses for a large number of effective siRNAs. In the proposed method, the score is defined as a gene degradation measure. The effectiveness for the proposed method was confirmed by evaluating effective and ineffective siRNAs for recently reported genes (12 genes, 172 siRNA sequences) and comparing with other reported scoring methods. The size (value) of this score is closely correlated with the degree of gene degradation, and the score can easily be used for selecting high-potential siRNA candidates. The evaluation results indicate that the proposed method would be useful for many other genes. It will therefore be useful for selecting siRNA sequences in mammalian genes.

Keywords: siRNA design; RNA interference; Gene-silencing; SOM classification; Statistical significance

Article Outline

1. Introduction
2. Materials and methods
2.1. The recently reported effective and ineffective siRNA sequences
2.2. 860 effective siRNA sequences
2.3. The self-organizing map for siRNA classification
2.4. Using the SOM to obtain siRNA sequence classifications
3. Results
3.1. siRNA sequence selections based on SOM and statistical significance analyses
3.2. siRNA sequence selection method
3.3. Verification of the effectiveness of the proposed method
3.3.1. Evaluation for the recently reported siRNA sequences
3.3.2. Comparison with other reported methods
4. Discussion
4.1. Relations between our previously reported and present methods
4.2. Suitability of the proposed method for use with a large number of effective siRNAs
Appendix A. Supplementary data
References









 
Home
Browse
My Settings
Alerts
Help
Elsevier.com (Opens new window)
About ScienceDirect  |  Contact Us  |  Information for Advertisers  |  Terms & Conditions  |  Privacy Policy
Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.