Demo Data from VLDB 2026 / reviewers in the wild / expert
Inbal Sela-Culang
dblp:161/2870
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—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 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › immunoinformatics › epitope prediction
b-cell epitope prediction |
0.2 | 1 | 2015 | PEASE: predicting B-cell epitopes utilizing antibody sequence · Bioinform. 2015 |
Bioinformatics and computational biology › immunoinformatics
epitope prediction |
0.2 | 1 | 2015 | PEASE: predicting B-cell epitopes utilizing antibody sequence · Bioinform. 2015 |
Bioinformatics and computational biology
immunoinformatics |
0.2 | 1 | 2015 | PEASE: predicting B-cell epitopes utilizing antibody sequence · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
sequence-based prediction · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | PEASE: predicting B-cell epitopes utilizing antibody sequenceabstractUNLABELLED: Antibody epitope mapping is a key step in understanding antibody-antigen recognition and is of particular interest for drug development, diagnostics and vaccine design. Most computational methods for epitope prediction are based on properties of the antigen sequence and/or structure, not taking into account the antibody for which the epitope is predicted. Here, we introduce PEASE, a web server predicting antibody-specific epitopes, utilizing the sequence of the antibody. The predictions are provided both at the residue level and as patches on the antigen structure. The tradeoff between recall and precision can be tuned by the user, by changing the default parameters. The results are provided as text and HTML files as well as a graph, and can be viewed on the antigen 3D structure. AVAILABILITY AND IMPLEMENTATION: PEASE is freely available on the web at www.ofranlab.org/PEASE. CONTACT: [email protected]. Inbal Sela-Culang, Shaul Ashkenazi, Björn Peters, Yanay Ofran |
Bioinform. | 1 |