Demo Data from SIGIR 2026 / reviewers in the wild / expert
Fabien Mareuil
dblp:84/9718
· DBLP profile ↗
4ranked-venue papers
2as first author
2since 2021 · last 2024
0000-0002-3832-9157ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 2 first-author · 2 since 2021Systems, architecture and hardware · 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
3 papers |
Bioinformatics and computational biology · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 9 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
drug discovery |
1.3 | 2 | 2024 | Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets · Bioinform. 2024 The iPPI-DB initiative: a community-centered database of protein-protein interaction modulators · Bioinform. 2021 |
Bioinformatics and computational biology › structural bioinformatics › ligand binding site analysis
binding pocket prediction |
0.8 | 1 | 2024 | Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets · Bioinform. 2024 |
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction analysis |
0.8 | 1 | 2024 | Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets · Bioinform. 2024 |
Bioinformatics and computational biology
structural bioinformatics |
0.8 | 1 | 2024 | Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets · Bioinform. 2024 |
Bioinformatics and computational biology › molecular informatics
cheminformatics |
0.5 | 1 | 2021 | The iPPI-DB initiative: a community-centered database of protein-protein interaction modulators · Bioinform. 2021 |
Bioinformatics and computational biology
protein structure analysis |
0.2 | 1 | 2024 | Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pockets · Bioinform. 2024 |
Bioinformatics and computational biology › structural biology
NMR structure calculation |
0.1 | 1 | 2011 | Grid computing for improving conformational sampling in NMR structure calculation · Bioinform. 2011 |
Bioinformatics and computational biology › structural bioinformatics
protein structure determination |
0.1 | 1 | 2011 | Grid computing for improving conformational sampling in NMR structure calculation · Bioinform. 2011 |
Distributed systems
grid computing |
0.0 | 1 | 2011 | Grid computing for improving conformational sampling in NMR structure calculation · Bioinform. 2011 |
Methods — techniques the papers use, named apart from their topics
crowdsourcing curation · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Protein interaction explorer (PIE): a comprehensive platform for navigating protein-protein interactions and ligand binding pocketsabstractSUMMARY: Protein Interaction Explorer (PIE) is a new web-based tool integrated to our database iPPI-DB, specifically crafted to support structure-based drug discovery initiatives focused on protein-protein interactions (PPIs). Drawing upon extensive structural data encompassing thousands of heterodimer complexes, including those with successful ligands, PIE provides a comprehensive suite of tools dedicated to aid decision-making in PPI drug discovery. PIE enables researchers/bioinformaticians to identify and characterize crucial factors such as the presence of binding pockets or functional binding sites at the interface, predicting hot spots, and foreseeing similar protein-embedded pockets for potential repurposing efforts. AVAILABILITY AND IMPLEMENTATION: PIE is user-friendly and readily accessible at https://ippidb.pasteur.fr/targetcentric/. It relies on the NGL visualizer. Fabien Mareuil, Alexandra Moine-Franel, Anuradha Kar, Michael Nilges, Constantin Bogdan Ciambur, Olivier Sperandio |
Bioinform. | 1 |
| 2021 | The iPPI-DB initiative: a community-centered database of protein-protein interaction modulatorsabstractMOTIVATION: One avenue to address the paucity of clinically testable targets is to reinvestigate the druggable genome by tackling complicated types of targets such as Protein-Protein Interactions (PPIs). Given the challenge to target those interfaces with small chemical compounds, it has become clear that learning from successful examples of PPI modulation is a powerful strategy. Freely accessible databases of PPI modulators that provide the community with tractable chemical and pharmacological data, as well as powerful tools to query them, are therefore essential to stimulate new drug discovery projects on PPI targets. RESULTS: Here, we present the new version iPPI-DB, our manually curated database of PPI modulators. In this completely redesigned version of the database, we introduce a new web interface relying on crowdsourcing for the maintenance of the database. This interface was created to enable community contributions, whereby external experts can suggest new database entries. Moreover, the data model, the graphical interface, and the tools to query the database have been completely modernized and improved. We added new PPI modulators, new PPI targets and extended our focus to stabilizers of PPIs as well. AVAILABILITY AND IMPLEMENTATION: The iPPI-DB server is available at https://ippidb.pasteur.fr The source code for this server is available at https://gitlab.pasteur.fr/ippidb/ippidb-web/ and is distributed under GPL licence (http://www.gnu.org/licences/gpl). Queries can be shared through persistent links according to the FAIR data standards. Data can be downloaded from the website as csv files. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Rachel Torchet, Karen Druart, Luis Checa Ruano, Alexandra Moine-Franel, Hélène Borges, Olivia Doppelt-Azeroual, Bryan Brancotte, Fabien Mareuil, Michael Nilges, Hervé Ménager, Olivier Sperandio |
Bioinform. | 8 |
| 2017 | Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities
Sarah Cohen Boulakia, Khalid Belhajjame, Olivier Collin, Jérôme Chopard, Christine Froidevaux, Alban Gaignard, Konrad Hinsen, Pierre Larmande, Yvan Le Bras, Frédéric Lemoine 0002, Fabien Mareuil, Hervé Ménager, Christophe Pradal, Christophe Blanchet |
Future Gener. Comput. Syst. | 11 |
| 2011 | Grid computing for improving conformational sampling in NMR structure calculationabstractMOTIVATION: Methods for automatic nuclear magnetic resonance (NMR) structure determination need to face a high level of ambiguity encountered in NMR spectra recorded by solid-state NMR and by solution NMR of partially unfolded proteins, leading to time-consuming calculations. The software package Ambiguous Restraints for Iterative Assignment (ARIA) allows for straightforward parallelization of the calculation, as the conformers can be generated in parallel on many nodes. RESULTS: Due to its architecture, the adaptation of ARIA to grid computing can be easily achieved by using the middleware glite and JDL (Job Description Language) scripts. This adaptation makes it possible to address highly ambiguous datasets, because of the much larger conformational sampling that can be generated by use of the grid computational power. AVAILABILITY: The version 2.3.1 of ARIA implemented on the grid is freely available from the ARIA web site: aria.pasteur.fr/downloads. Fabien Mareuil, Christophe Blanchet, Therese E. Malliavin, Michael Nilges |
Bioinform. | 1 |