Name
Abstract | ||
|---|---|---|
This paper describes a fast and fully automated dictionary-based approach to gene annotation and exon prediction. Two dictionaries are constructed, one from the nonredundant protein OWL database and the other from the dbEST database. These dictionaries are used to obtain O (1) time lookups of tuples in the dictionaries (4 tuples for the OWL database and 11 tuples for the dbEST database). These tuples can be used to rapidly find the longest matches at every position in an input sequence to the database sequences. Such matches provide very useful information pertaining to locating common segments between exons, alternative splice sites, and frequency data of long tuples for statistical purposes. These dictionaries also provide the basis for both homology determination, and statistical approaches to exon prediction. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1089/106652799318364 | Journal of Computational Biology |
Keywords | Field | DocType |
gene recognition,splice site detection,gene annotation,exon prediction,alternative splicing,structure alignment,sequence,amino acid,nucleotides,fold recognition,protein threading | Structural alignment,Tuple,Computer science,Threading (protein sequence),Alternative Splice Sites,Bioinformatics,Inverse folding,Gene Annotation | Conference |
Volume | Issue | ISSN |
6 | 3-4 | 1066-5277 |
ISBN | Citations | PageRank |
1-58113-069-4 | 9 | 7.23 |
References | Authors | |
8 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lior Pachter | 1 | 1026 | 121.08 |
| Serafim Batzoglou | 2 | 806 | 85.80 |
| Valentin I. Spitkovsky | 3 | 362 | 28.64 |
| Eric Banks | 4 | 9 | 7.23 |
| Eric S Lander | 5 | 434 | 100.07 |
| Daniel J. Kleitman | 6 | 854 | 277.98 |
| Bonnie Berger | 7 | 1643 | 165.84 |