NDLI: Evaluation of RNA Secondary Structure Motifs using Regression Analysis

Content Provider	IEEE Xplore Digital Library
Author	Anwar, M. Turcotte, M.
Copyright Year	2006
Description	Author affiliation: Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont. (Anwar, M.; Turcotte, M.)
Abstract	Recent experimental evidences have shown that ribonucleic acid (RNA) plays a greater role in the cell than previously thought. An ensemble of RNA sequences believed to contain signals at the structure level can be exploited to detect functional motifs common to all or a portion of those sequences. We present here a general framework for analyzing multiple RNA secondary structures. A family of related RNA structures may be analyzed using statistical regression methods. In this work, we extend our previously developed algorithm, seed, that allows to explore exhaustively the search space of RNA sequence and structure motifs. We introduce here several objective functions based on thermodynamic free energy and information content to discriminate native folds from the rest. We assume that the variation across the various scores can be represented by a statistical model. Regression analysis permits to assign separate weight for each score, allowing one to emphasize or compensate the variance that differs across the different scores. A statistical model can be formulated using techniques from regression analysis to obtain a template or scoring model that is able to identify putative functional regions in RNA sequences. We show that thermodynamic based regression models are effective to associate the variation of scores obtained from different functions. The models can generally identify motifs with high measures of specificity and positive predicted value to known motifs. A good scoring method will allow to eliminate invalid motifs thereby reducing the size of the hypothesis space
Starting Page	1747
Ending Page	1752
File Size	178380
Page Count	6
File Format	PDF
ISBN	1424400384
DOI	10.1109/CCECE.2006.277314
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-05-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	RNA Regression analysis Sequences Thermodynamics Information technology Genetics Biological information theory Biology computing Nearest neighbor searches Accuracy linear regression Motif discovery ribonucleic acid secondary structure thermodynamics
Content Type	Text
Resource Type	Article

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