compPknots: A Framework for Parallel Prediction and Comparison of RNA Secondary Structures with Pseudoknots
Author(s) -
Trilce Estrada,
Abel Licon,
Michela Taufer
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-49860-5
DOI - 10.1007/11942634_70
Subject(s) - computer science , strengths and weaknesses , simple (philosophy) , data mining , theoretical computer science , epistemology , philosophy
Codes for RNA secondary structure prediction based on energy minimization are usually time and resource intensive. For this reason several codes have been simplified: in some cases they do not predict complex structures like pseudoknots, other times they predict structures with reduced lengths, or with simple pseudoknots. Each of these codes has its strengths and weaknesses. Providing scientists with tools that combine the strengths of the several codes is a worthwhile objective. To address this need, we present compPknots, a parallel framework that uses a combination of existing codes like Pknots-RE and Pknots-RG, to predict RNA secondary structures concurrently and automatically compare them with reference structures from databases or literature. In this paper compPknots is used to compare the predictions of 217 RNA structures from the PseudoBase database. Its parallel master-slave architecture provide scientists with higher prediction accuracies in shorter time.
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