Demo Data from EDBT 2026 / reviewers in the wild / expert
R. N. Curnow
dblp:59/123
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1989
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 56% Computational science and engineering · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis › sequence similarity search
sequence database search |
0.0 | 1 | 1989 | A test for the statistical significance of DNA sequence similarities for application in databank searches · Comput. Appl. Biosci. 1989 |
Computational science and engineering
statistical significance testing |
0.0 | 1 | 1989 | A test for the statistical significance of DNA sequence similarities for application in databank searches · Comput. Appl. Biosci. 1989 |
Bioinformatics and computational biology › sequence analysis
sequence similarity |
0.0 | 1 | 1989 | A test for the statistical significance of DNA sequence similarities for application in databank searches · Comput. Appl. Biosci. 1989 |
Methods — techniques the papers use, named apart from their topics
word searching · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1989 | A test for the statistical significance of DNA sequence similarities for application in databank searchesabstractA method is developed, based on word-searching, which provides a rapid test for the statistical significance of DNA sequence similarities for use in databank searching. The method makes allowance for the lengths and dinucleotide compositions of the sequences being compared. A way is also described to calculate the power of the test, i.e. the probability of detecting a given similarity as being statistically significant. The effects on the power of the test of the scoring method, word length, sequence length, and sequence composition are examined. A novel scoring method is shown to be superior to the method currently used in most word-searching algorithms. R. F. Mott, Thomas B. L. Kirkwood, R. N. Curnow |
Comput. Appl. Biosci. | 3 |