Table 2.
Genome Analysis Programs for Identifying Characteristic Features of Unknown DNA Sequences
| Program Name | Type of Annotation | Program Location | Program Information |
|---|---|---|---|
| Homology Searches | |||
| Repeats | Repeat Finder | Local | NCBI Repeats Database (http://repeatmasker.genome.washington.edu/cgi-bin/RM2_req.pl) |
| DbEST | Homology Search against EST database | Remote (Network-Client) | NCBI EST Database using Blastc13 (http://www.ncbi.nlm.nih.gov/BLAST) |
| Spliced ESTs | — | Local | Groups ESTs originated from a single clone |
| GenPept | Homology Search against NCBI protein database | Remote (Network-Client) | NCBI Protein Database using Blastc13 (http://www.ncbi.nlm.nih.gov/BLAST) |
| Exon Prediction | |||
| Xpound | Gene Finder (rule-based) | Local | Software for exon trapping based on maximum likelihood methods (Kamb et al. 1995) |
| MZEF | Gene Finder (rule-based) | Local | Predicts putative internal protein coding exons in genomic DNA sequences, starts with potential exon and calculates posterior exon probability (Zhang 1997, 1998) |
| GrailEXP | Gene Finder (neural network) | Web Server | Incorporates EST homology searches and biological rules to model more complicated gene structures (http://compbio.ornl.gov/grailexp) (Xu et al. 1997) |
| GeneID | Gene Finder (neural network) | Local | Uses hierarchical structure to first identify splice sites, start and stop codons, then build exons, followed by scoring of exons and assembling gene structure (Parra et at. 2000) |
| Eukaryotic GeneMark.hmm | Gene Finder [Hidden Markov Model (HMM)] | Web Server | Relies upon an Inhomogeneous Markov Model approach combined with training data sets to predict genes (http://www.genemark.biology.gatech.edu/GeneMark/hum.cgi) |
| GENSCAN | Gene Finder (HMM) | Local | Uses general probabilistic model of gene structure assembling knowledge of basic transcriptional, translational, and splicing signals to predict exons (Burge and Karlin 1997) |
| Fgenesh | Gene Finder (HMM) | Local | Combines pattern recognition features with similarity searches of predicted exons against known protein databases (Solovyev and Salamov 1997) |
| Other Analyses | |||
| ORF Finder | Open Reading Frame Finder | Web Server | http://www.ncbi.nih.gov/gorf/gorf.html |
| NNPP | Promoter Prediction | Local | Neural Network Promoter Prediction (NNPP) uses time-delay to predict promoters |
| Promoter-Inspector | Promoter Prediction | Web Server | Accurately predicts 43 percent of true promoters (http://genomatix.gsf.de/cgi-bin/promoterinspector/promoterinspector.pl) (Scherf et al. 2000) |
| GrailEXP CpG islands | CpG Island Finder | Web Server | Identifies regions containing short (200–2000bp) segments with a characteristic DNA composition (i.e., a GC content greater than 50 percent) that are commonly located near the starting regions of genes (http://compbio.ornl.gov/grailexp) (Xu et al. 1997) |
NOTE: The results of these analyses can be entered into the Genotator program for a comprehensive analysis of unknown DNA sequences.