Table 1.
Comparison of running FindGDPs and GDPFinder (Talaat et al., 2000) on four different, annotated microbial genomes.
| Organism and Reference | Number of ORFsa | FindGDPs | GDPFinder | ||
|---|---|---|---|---|---|
| Runtime (sec)b | Number of GDPsc | Runtime (sec)b | Number of GDPsd | ||
| Escherichia coli K12 www.genome.wisc.edu | 4290 | 30 | 76 | 1248 | 136 |
| Streptococcus pneumoniae TIGR4 www.tigr.org | 2236 | 15 | 67 | 492 | 117 |
| Haemophilus infuenzae KW20 www.tigr.org | 1738 | 11 | 40 | 394 | 66 |
| Mycoplasma genitalium G-37 www.tigr.org | 483 | 3 | 17 | 123 | 20 |
a
The number of annotated genes in the given genome that were predicted to encode proteins.
b
Test system was an 866MHz Pentium III with 256MB of memory running Microsoft Windows 2000.
c
The number of 6-nucleotide GDPs, as identified by FindGDPs, that bind to the 3′ 30% of all annotated protein-encoding ORFs and that do not exhibit full-length complementarity to the 5S, 16S, or 23S rRNA sequences annotated in the genome of the corresponding organism.
d
The number of 6-nucleotide GDPs, as identified by the Fast Find GDPs algorithm of GDPFinder (Talaat et al., 2000), that bind to the 3’ 30% of all annotated protein-encoding ORFs.