Demo Data from SIGIR 2026 / reviewers in the wild / expert
D. S. Tuckwell
dblp:28/1404
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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 · 100% |
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 › multiple sequence alignment
multiple sequence alignment analysis |
0.0 | 1 | 1995 | Protein secondary structure prediction by the analysis of variation and conservation in multiple alignments · Comput. Appl. Biosci. 1995 |
Bioinformatics and computational biology
protein structure prediction |
0.0 | 1 | 1995 | Protein secondary structure prediction by the analysis of variation and conservation in multiple alignments · Comput. Appl. Biosci. 1995 |
Bioinformatics and computational biology › protein structure prediction
secondary structure prediction |
0.0 | 1 | 1995 | Protein secondary structure prediction by the analysis of variation and conservation in multiple alignments · Comput. Appl. Biosci. 1995 |
Methods — techniques the papers use, named apart from their topics
variation/conservation analysis · 0.0consensus prediction · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Protein secondary structure prediction by the analysis of variation and conservation in multiple alignmentsabstractA number of methods exist for the prediction of protein secondary structure from primary sequence. One method identifies variable charged and conserved hydrophobic residues within large multiple alignments as a means of indicating outside and inside sites respectively in the protein structure. These sites are then manually fitted to secondary structure templates to generate a secondary structure prediction. Using the existing theoretical bases of this method, we present an algorithm (STAMA) which automatically carries out the initial variation/conservation analysis of the alignment. We also test the accuracy of complete predictions carried out by manual fitting of the STAMA-derived assignments to structure templates, using five large multiple alignments each including a protein of known structure. The method was found on average to predict only 57% of residues in the correct secondary structure, and was only as accurate as predictions carried out using the established and automated method of Garnier, Osguthorpe and Robson (1978) applied to a single sequence. When used in conjunction with other secondary structure prediction methods, however, the resulting consensus predictions were found to be very accurate, with 78% of the elements (alpha helices or beta strands) for which a consensus could be obtained being predicted correctly. The algorithm presented here, plus the assessment of the accuracy of prediction generated by this method, should enable this predictive approach to receive informed general use. D. S. Tuckwell, M. J. Humphries, Andy Brass |
Comput. Appl. Biosci. | 1 |