The performance of gene-predicting tools varies considerably if evaluated with 
respect to the parameters sensitivity and specificity or their capability to 
identify the correct start codon. We were interested to validate tools for gene 
prediction and to implement a metatool named YACOP, which combines existing 
tools and has a higher performance. YACOP parses and combines the output of the 
three gene-predicting systems Criticia, Glimmer and ZCURVE. It outperforms each 
of the programs tested with its high sensitivity and specificity values combined 
with a larger number of correctly predicted gene starts. Performance of YACOP 
and the gene-finding programs was tested by comparing their output with a 
carefully selected set of annotated genomes. We found that the problem of 
identifying genes in prokaryotic genomes by means of computational analysis was 
solved satisfactorily. In contrast, the correct localization of the start codon 
still appeared to be a problem, as in all cases under test at least 7.8% and up 
to 32.3% of the positions given in the annotations differed from the locus 
predicted by any of the programs tested. YACOP can be downloaded from 
http://www.g2l.bio.uni-goettingen.de.