This program predicts potential microRNA targets using an estimated free energy of binding.
This program predicts acquired genes by re-ranking the matches in BLAST search based on their species relationships with the query [ 20].
This program predicts highly reliable Helitrons on the basis of a strict consensus to the short, conserved terminal ends of the experimentally determined Hel1 family (Dooner and He 2008).
This program predicts the presence of ESE motifs based on a list of 238 hexamer motifs found to be significantly enriched in exonic sequence, when compared with intronic sequence, and significantly enriched in exons with weak splice signals compared with exons with strong splice signals.
This program predicts sRNAs within the intergenic regions of bacterial genomes by searching for Rho-independent terminators downstream of conserved sequences, followed by an analysis of conservation with other species, potential transcription factor binding sites, the spacing between flanking genes, and homology with known sRNAs [ 26].
With this strategy, the program predicted reliable full-length LTR retrotransposons in two genomes.
For this region the program predicted seven glucocorticoid-response elements, nine retinoid-response elements [both retinoid X receptor (RXR) and RA receptor (RAR)], three oestrogen-response elements and two progesterone-response elements.
With an acceptable probability (E-value 0.095), the program predicted an exon in this intron 6 (at location 3271 3381).
When the scientists fed Jones's album into that computer, alarm bells went off: the program predicted that eight tracks would hit the charts.
Scanning the content of nearly 44,000 photos from 166 participants, the program predicted clinical depression diagnoses by parsing facial detection data, platform activity metrics, metadata, and color analysis.
