A comprehensive comparison of comparative RNA structure prediction approaches.
BACKGROUND
An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene-finding and multiple-sequence-alignment algorithms.


RESULTS
Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance.


CONCLUSIONS
We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms of both sensitivity and selectivity across different lengths and homologies. Furthermore, we outline some directions for future research.
Department of Evolutionary Biology, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark. PPGardner@bi.ku.dk
Paul P
PP
Gardner
Robert
R
Giegerich
D000465:Algorithms; D019985:Benchmarking / Q000379:methods; D016384:Consensus Sequence / Q000235:genetics; D048168:Escherichia coli K12 / Q000235:genetics; D009690:Nucleic Acid Conformation; D011237:Predictive Value of Tests; D012313:RNA / Q000235:genetics*; D012329:RNA, Bacterial / Q000235:genetics; D012331:RNA, Fungal; D012441:Saccharomyces cerevisiae / Q000235:genetics; D016415:Sequence Alignment / Q000379:methods; D012984:Software; D012985:Software Design
D012329:RNA, Bacterial; D012331:RNA, Fungal; D012313:RNA