Computational prediction of microRNAs encoded in viral and other genomes.
We present an overview of selected computational methods for microRNA prediction. It is especially aimed at viral miRNA detection. As the number of microRNAs increases and the range of genomes encoding miRNAs expands, it seems that these small regulators have a more important role than has been previously thought. Most microRNAs have been detected by cloning and Northern blotting, but experimental methods are biased towards abundant microRNAs as well as being time-consuming. Computational detection methods must therefore be refined to serve as a faster, better, and more affordable method for microRNA detection. We also present data from a small study investigating the problems of computational miRNA prediction. Our findings suggest that the prediction of microRNA precursor candidates is fairly easy, while excluding false positives as well as exact prediction of the mature microRNA is hard. Finally, we discuss possible improvements to computational microRNA detection.
Thomassen
Gard O S
GO
Centre for Molecular Biology and Neuroscience (CMBN), Institute of Medical Microbiology, Rikshospitalet-Radiumhospitalet Medical Centre, 0027 Oslo, Norway.
Røsok
Oystein
O
Rognes
Torbjørn
T