A Detailed Analysis of Parallel Speedup in P-RnaPredict - An Evolutionary Algorithm for RNA Secondary Structure Prediction

Abstract

The function of an RNA molecule is primarily established by its physical shape. As current physical structure determination methods are time consuming and expensive, there is great interest in finding computational structure prediction methods. P-RnaPredict is a parallel evolutionary algorithm for RNA secondary structure prediction. Two sets of experiments are performed on 5 known structures from 3 RNA classes (5S rRNA, Group I intron 16S rRNA, and 16S rRNA). The first determines the actual speedup, and the second evaluates the performance of P-RnaPredict through comparison to mfold. PRnaPredict succeeds in predicting structures with higher true positive base pair counts and lower false positives than mfold on specific sequences.