Demo Data from VLDB 2026 / reviewers in the wild / expert
Francis Rodier
dblp:96/2837
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—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 · 67% Computational science and engineering · 33% |
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
machine learning classification |
0.1 | 1 | 2008 | DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological protein-protein interactions · Bioinform. 2008 |
Bioinformatics and computational biology › protein analysis
protein-protein interaction |
0.1 | 1 | 2008 | DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological protein-protein interactions · Bioinform. 2008 |
Computational science and engineering › computational geometry
voronoi tessellation |
0.1 | 1 | 2008 | DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological protein-protein interactions · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
voronoi tessellation · 0.1machine learning · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological protein-protein interactionsabstractMOTIVATION: Knowledge of the oligomeric state of a protein is often essential for understanding its function and mechanism. Within a protein crystal, each protein monomer is in contact with many others, forming many small interfaces and a few larger ones that are biologically significant if the protein is a homodimer in solution, but not if the protein is monomeric. Telling such 'crystal dimers' from real ones remains a difficult task. RESULTS: It has already been demonstrated that the interfaces of native and non-native protein-protein complexes can be distinguished using a combination of parameters computed with a method on the Voronoi tessellation. We show in this article that the same parameters highlight significant differences between the interfaces of biological and crystal dimers. Using these parameters as descriptors in machine learning methods leads to accurate classification of specific and non-specific protein-protein interfaces. AVAILABILITY: Software is available at http://fifi.ibbmc.u-psud.fr/DiMoVo. Julie Bernauer, Ranjit Prasad Bahadur, Francis Rodier, Joël Janin, Anne Poupon |
Bioinform. | 3 |