Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars

Background: The prediction of the structure of large RNAs remains a particular challenge in bioinformatics, due to the computational complexity and low levels of accuracy of state-of-the-art algorithms. The pfold model couples a stochastic context-free grammar to phylogenetic analysis for a high accuracy in predictions, but the time complexity of the algorithm and underflow errors have prevented its use for long alignments. Here we present PPfold, a multithreaded version of pfold, which is capable of predicting the structure of large RNA alignments accurately on practical timescales. Results: We have distributed both the phylogenetic calculations and the inside-outside algorithm in PPfold, resulting in a significant reduction of runtime on multicore machines. We have addressed the floating-point underflow problems of pfold by implementing an extended-exponent datatype, enabling PPfold to be used for large-scale RNA structure predictions. We have also improved the user interface and po...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Zsuzsanna Sukosd, Bjarne Knudsen, Morten Vaerum, Jorgen Kjems, Ebbe Sloth Andersen
• Keywords: Algorithms, Artificial Intelligence, BMCBI 2011, Large Rna, Predictions