Demo Data from VLDB 2026 / reviewers in the wild / expert
Trevor D. Power
dblp:58/6356
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—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 · 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 › protein-protein interaction prediction
protein interface prediction |
0.1 | 1 | 2007 | InterProSurf: a web server for predicting interacting sites on protein surfaces · Bioinform. 2007 |
Bioinformatics and computational biology › structural biology › protein structure and function
protein structure and function prediction |
0.1 | 1 | 2007 | InterProSurf: a web server for predicting interacting sites on protein surfaces · Bioinform. 2007 |
Bioinformatics and computational biology
structural bioinformatics |
0.0 | 1 | 2007 | InterProSurf: a web server for predicting interacting sites on protein surfaces · Bioinform. 2007 |
Methods — techniques the papers use, named apart from their topics
solvent accessible surface area · 0.1interface propensity · 0.1clustering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | InterProSurf: a web server for predicting interacting sites on protein surfacesabstractUNLABELLED: A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments. AVAILABILITY: The InterProSurf web server is available at http://curie.utmb.edu/ Surendra S. Negi, Catherine H. Schein, Numan Oezguen, Trevor D. Power, Werner Braun |
Bioinform. | 4 |