Demo Data from EDBT 2026 / reviewers in the wild / expert
Fabien Fontaine
dblp:140/8965
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › proteomics
peptide analysis |
0.4 | 1 | 2019 | WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source · Bioinform. 2019 |
Bioinformatics and computational biology › proteomics › post-translational modification site prediction
protease cleavage site prediction |
0.4 | 1 | 2019 | WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source · Bioinform. 2019 |
Bioinformatics and computational biology
proteomics |
0.4 | 1 | 2019 | WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source · Bioinform. 2019 |
Bioinformatics and computational biology › drug discovery
drug design |
0.1 | 1 | 2019 | WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
similarity scoring · 0.4frequency analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data sourceabstractSUMMARY: More than 150 peptide therapeutics are globally in clinical development. Many enzymatic barriers should be crossed by a successful drug to be prosperous in such a process. Therefore, the new peptide drugs must be designed preventing the potential protease cleavage to make the compound less susceptible to protease reaction. We present a new data analysis tool developed in WebMetabase, an approach that stores the information from liquid chromatography mass spectrometry-based experimental data or from external sources such as the MEROPS database. The tool is a chemically aware system where each peptide substrate is presented as a sequence of structural blocks (SBs) connected by amide bonds and not being limited to the natural amino acids. Each SB is characterized by its pharmacophoric and physicochemical properties including a similarity score that describes likelihood between a SB and each one of the other SBs in the database. This methodology can be used to perform a frequency analysis to discover the most frequent cleavage sites for similar amide bonds, defined based on the similarity of the SB that participate in such a bond within the experimentally derived and/or public database. AVAILABILITY AND IMPLEMENTATION: http://webmetabase.com:8182/WebMetabaseBioinformatics/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Tatiana Radchenko, Fabien Fontaine, Luca Morettoni, Ismael Zamora |
Bioinform. | 2 |