BACKGROUND: The ENCODE gene prediction workshop (EGASP) has been organized to 
evaluate how well state-of-the-art automatic gene finding methods are able to 
reproduce the manual and experimental gene annotation of the human genome. We 
have used Softberry gene finding software to predict genes, pseudogenes and 
promoters in 44 selected ENCODE sequences representing approximately 1% (30 Mb) 
of the human genome. Predictions of gene finding programs were evaluated in 
terms of their ability to reproduce the ENCODE-HAVANA annotation.
RESULTS: The Fgenesh++ gene prediction pipeline can identify 91% of coding 
nucleotides with a specificity of 90%. Our automatic pseudogene finder (PSF 
program) found 90% of the manually annotated pseudogenes and some new ones. The 
Fprom promoter prediction program identifies 80% of TATA promoters sequences 
with one false positive prediction per 2,000 base-pairs (bp) and 50% of 
TATA-less promoters with one false positive prediction per 650 bp. It can be 
used to identify transcription start sites upstream of annotated coding parts of 
genes found by gene prediction software.
CONCLUSION: We review our software and underlying methods for identifying these 
three important structural and functional genome components and discuss the 
accuracy of predictions, recent advances and open problems in annotating genomic 
sequences. We have demonstrated that our methods can be effectively used for 
initial automatic annotation of the eukaryotic genome.