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Maxime Chazalviel

dblp:212/0298 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0003-1534-612XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems biology
metabolic network analysis
0.422019
MetExploreViz: web component for interactive metabolic network visualization · Bioinform. 2018
MetaboRank: network-based recommendation system to interpret and enrich metabolomics results · Bioinform. 2019
Bioinformatics and computational biology › metabolomics
metabolite identification
0.412019
MetaboRank: network-based recommendation system to interpret and enrich metabolomics results · Bioinform. 2019
Bioinformatics and computational biology
metabolomics
0.412019
MetaboRank: network-based recommendation system to interpret and enrich metabolomics results · Bioinform. 2019
Bioinformatics and computational biology › network bioinformatics › biological network analysis
network visualization
0.312018
MetExploreViz: web component for interactive metabolic network visualization · Bioinform. 2018
Bioinformatics and computational biology
omics data analysis
0.112018
MetExploreViz: web component for interactive metabolic network visualization · Bioinform. 2018

Methods — techniques the papers use, named apart from their topics

network-based recommendation · 0.4graph-based recommendation · 0.4web component · 0.3
YearPublicationVenuePosition
2019 MetaboRank: network-based recommendation system to interpret and enrich metabolomics results
abstract
Motivation: Metabolomics has shown great potential to improve the understanding of complex diseases, potentially leading to therapeutic target identification. However, no single analytical method allows monitoring all metabolites in a sample, resulting in incomplete metabolic fingerprints. This incompleteness constitutes a stumbling block to interpretation, raising the need for methods that can enrich those fingerprints. We propose MetaboRank, a new solution inspired by social network recommendation systems for the identification of metabolites potentially related to a metabolic fingerprint. Results: MetaboRank method had been used to enrich metabolomics data obtained on cerebrospinal fluid samples from patients suffering from hepatic encephalopathy (HE). MetaboRank successfully recommended metabolites not present in the original fingerprint. The quality of recommendations was evaluated by using literature automatic search, in order to check that recommended metabolites could be related to the disease. Complementary mass spectrometry experiments and raw data analysis were performed to confirm these suggestions. In particular, MetaboRank recommended the overlooked α-ketoglutaramate as a metabolite which should be added to the metabolic fingerprint of HE, thus suggesting that metabolic fingerprints enhancement can provide new insight on complex diseases. Availability and implementation: Method is implemented in the MetExplore server and is available at www.metexplore.fr. A tutorial is available at https://metexplore.toulouse.inra.fr/com/tutorials/MetaboRank/2017-MetaboRank.pdf. Supplementary information: Supplementary data are available at Bioinformatics online.
Clément Frainay, Sandrine Aros, Maxime Chazalviel, Thomas Garcia, Florence Vinson, Nicolas Weiss, Benoit Colsch, Frédéric Sedel, Dominique Thabut, Christophe Junot, Fabien Jourdan
Bioinform.3
2018 MetExploreViz: web component for interactive metabolic network visualization
abstract
SUMMARY: MetExploreViz is an open source web component that can be easily embedded in any web site. It provides features dedicated to the visualization of metabolic networks and pathways and thus offers a flexible solution to analyse omics data in a biochemical context. AVAILABILITY AND IMPLEMENTATION: Documentation and link to GIT code repository (GPL 3.0 license) are available at this URL: http://metexplore.toulouse.inra.fr/metexploreViz/doc/.
Maxime Chazalviel, Clément Frainay, Nathalie Poupin, Florence Vinson, Benjamin Merlet, Yoann Gloaguen, Ludovic Cottret, Fabien Jourdan
Bioinform.1