Document Detail


RFRCDB-siRNA: improved design of siRNAs by random forest regression model coupled with database searching.
MedLine Citation:
PMID:  17644215     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Although the observations concerning the factors which influence the siRNA efficacy give clues to the mechanism of RNAi, the quantitative prediction of the siRNA efficacy is still a challenge task. In this paper, we introduced a novel non-linear regression method: random forest regression (RFR), to quantitatively estimate siRNAs efficacy values. Compared with an alternative machine learning regression algorithm, support vector machine regression (SVR) and four other score-based algorithms [A. Reynolds, D. Leake, Q. Boese, S. Scaringe, W.S. Marshall, A. Khvorova, Rational siRNA design for RNA interference, Nat. Biotechnol. 22 (2004) 326-330; K. Ui-Tei, Y. Naito, F. Takahashi, T. Haraguchi, H. Ohki-Hamazaki, A. Juni, R. Ueda, K. Saigo, Guidelines for the selection of highly effective siRNA sequences for mammalian and chick RNA interference, Nucleic Acids Res. 32 (2004) 936-948; A.C. Hsieh, R. Bo, J. Manola, F. Vazquez, O. Bare, A. Khvorova, S. Scaringe, W.R. Sellers, A library of siRNA duplexes targeting the phosphoinositide 3-kinase pathway: determinants of gene silencing for use in cell-based screens, Nucleic Acids Res. 32 (2004) 893-901; M. Amarzguioui, H. Prydz, An algorithm for selection of functional siRNA sequences, Biochem. Biophys. Res. Commun. 316 (2004) 1050-1058) our RFR model achieved the best performance of all. A web-server, RFRCDB-siRNA (http://www.bioinf.seu.edu.cn/siRNA/index.htm), has been developed. RFRCDB-siRNA consists of two modules: a siRNA-centric database and a RFR prediction system. RFRCDB-siRNA works as follows: (1) Instead of directly predicting the gene silencing activity of siRNAs, the service takes these siRNAs as queries to search against the siRNA-centric database. The matched sequences with the exceeding the user defined functionality value threshold are kept. (2) The mismatched sequences are then processed into the RFR prediction system for further analysis.
Authors:
Peng Jiang; Haonan Wu; Yao Da; Fei Sang; Jiawei Wei; Xiao Sun; Zuhong Lu
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Publication Detail:
Type:  Journal Article     Date:  2007-07-17
Journal Detail:
Title:  Computer methods and programs in biomedicine     Volume:  87     ISSN:  0169-2607     ISO Abbreviation:  Comput Methods Programs Biomed     Publication Date:  2007 Sep 
Date Detail:
Created Date:  2007-08-13     Completed Date:  2007-11-13     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8506513     Medline TA:  Comput Methods Programs Biomed     Country:  Ireland    
Other Details:
Languages:  eng     Pagination:  230-8     Citation Subset:  IM    
Affiliation:
State Key Laboratory of Bioelectronics, Department of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Base Sequence
Data Interpretation, Statistical
Database Management Systems*
Databases, Genetic*
Information Storage and Retrieval / methods
Models, Genetic
Molecular Sequence Data
RNA Interference
RNA, Small Interfering / genetics*
Regression Analysis
Sequence Analysis, RNA / methods*
Software*
Chemical
Reg. No./Substance:
0/RNA, Small Interfering

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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