About a month before a New York Academy of Sciences (NYAS) meeting last February, six of the scheduled speakers received an unusual homework assignment. Each was asked to apply the sequences of two animal microRNAs to an algorithm that his team had developed for predicting messenger RNA binding targets.
The assignment was aimed at making the NYAS meeting, which focused on such algorithms, "a bit more interesting," says organizer Thomas Tuschl, who heads Rockefeller University's laboratory of RNA molecular biology. But a side-by-side comparison of the bioinformatic strategies was also timely. Since 2001, researchers have combed through animal, plant, and viral genomes to ferret out hundreds of genes that encode microRNAs.1 Approximately 22 nucleotides long, these RNA snippets cause translational repression in animals after they bind to target sites in mRNAs' 3' untranslated regions (UTRs). During the past year, about half a dozen groups have reported on algorithms that generate ...
