Thomas Charlon Photo

Thomas Charlon, PhD

Research Associate in Biomedical Informatics

Thomas Charlon received his Master of Computer Engineering from EPITA, Le Kremlin-Bicetre, France (2013) and completed his Computer Science PhD at the University of Geneva, Switzerland (2019) while being employed as a Bioinformatician at Quartz Bio (Merck Serono spin-off, part of Precision for Medicine), to lead the genetic analysis of the EU-funded PreciseSADs project and develop new algorithms for clustering and sparse coding of genome-wide data in systemic autoimmune diseases.

He then independently researched withheld content on social networks in European countries, developed a novel topic modeling methodology, and pursued commercial projects as quantitative trading and developing a web application for real-estate price estimation using 10 years of French tax office open-data. He published multiple R packages for genetic analysis, social network analysis, density-based clustering, and graph visualization on Github and CRAN.

As a Research Associate in the CELEHS laboratory, he focuses on standardizing analysis processes, setting up implementation quality procedures, enhancing statistical visualizations used in web applications, and facilitating the dissemination of analyses results using web APIs. His research applies natural language processing to unstructured text data related to mental health and suicide prevention, as scientific publications and electronic health records, to assist psychiatrists and clinicians in identifying at-risk patients, develop new multidimensional diagnoses, and expand our understanding of mental health disorders.

Single Nucleotide Polymorphism Clustering in Systemic Autoimmune Diseases.
Authors: Charlon T, Martínez-Bueno M, Bossini-Castillo L, Carmona FD, Di Cara A, Wojcik J, Voloshynovskiy S, Martín J, Alarcón-Riquelme ME.
PLoS One
View full abstract on Pubmed
CRAN R package vignette
Authors: snplinkage: Single Nucleotide Polymorphism Linkage Disequilibrium Visualizations
2023.
2019.
Authors: Genetic clustering for the discovery of a new classification of systemic autoimmune diseases

CRAN R package vignette
Authors: OPTICS K-Xi Density-Based Clustering
2019.
F1000Research
Authors: Replication of the principal component analyses of the human genome diversity panel
2017; 6:278.