Name
Abstract | ||
|---|---|---|
The computer system ACTIVITY is intended for generating programs with which to predict the activity of functional sites by nucleotide sequences. ACTIVITY analyzes a basis set of nucleotide sequences with known activity. The novelty of this approach is that Zadeh's fuzzy logic and decision-making theory have been employed for determining the best "sequence --> activity" regression. The best one thus determined is then transformed into the text of a program with which the activity for any nucleotide sequence is to be predicted. Testing with independent data has proved this prediction reliable. We have compared our approach with the two commonly used on identical data sets to find the ACTIVITY-generated programs quite competitive. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1089/cmb.1997.4.83 | JOURNAL OF COMPUTATIONAL BIOLOGY |
Keywords | Field | DocType |
nucleotide sequence,functional site,activity,prediction,program generation | Data set,Regression,Nucleic acid sequence,Fuzzy logic,Artificial intelligence,Novelty,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
4.0 | 1 | 1066-5277 |
Citations | PageRank | References |
6 | 0.73 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mikhail P Ponomarenko | 1 | 131 | 27.97 |
| A. N. Kolchanova | 2 | 6 | 0.73 |
| Nikolay A. Kolchanov | 3 | 470 | 105.75 |