Name
Abstract | ||
|---|---|---|
Finite-state automata called transducers, which have both input and output, can be used to model sim- ple mechanisms of biological mutation. We present a methodology whereby numerically-weighted versions of such specifications can be mechanically adapted to create string edit machines that are essentially equiv- alent to recurrence relations of the sort that chat- acterize dynamic programming alignment algorithms. Based on this, we have developed a visual program- ruing system for designing new alignment algorithms in a rapid-prototyping fashion. |
Year | Venue | Keywords |
|---|---|---|
1995 | ISMB | finite state automata,visual programming,recurrence relation |
Field | DocType | Volume |
Computer science,Automation,Theoretical computer science,Input/output,Visual programming language,Software,Artificial intelligence,Dynamic programming,sort,Automaton,Markov chain,Algorithm,Bioinformatics,Machine learning | Conference | 3 |
ISSN | Citations | PageRank |
1553-0833 | 16 | 5.95 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David B. Searls | 1 | 314 | 171.53 |
| Michael Kuperberg | 2 | 7589 | 529.66 |