معرفی
Thomas Bigot is a researcher at the Bioinformatics and Biostatistics HUB of Institut Pasteur in Paris, France. He joined the institution in 2016 and is actively involved in the PAGE expertise group and maintains a privileged partnership with the Pathogen Discovery Laboratory. His work focuses on developing bioinformatics methods for pathogen detection from metagenomic data.
Dr. Bigot holds a PhD in Bioinformatics (2013) from the University of Lyon, France, where his research focused on detecting topological patterns in phylogenetic trees. He also earned a Master's degree in Health and Populations with a specialization in Bioinformatics, Biostatistics, and Genome from Université Lyon 1 in 2009. His doctoral work led to the development of a formalism for describing tree patterns and a software suite for executing queries on thousands of phylogenetic trees.
His research interests span bioinformatics, metagenomics, pathogen discovery, phylogenetics, and viral detection. As a developer proficient in Python and C++, he focuses on optimizing laboratory prototypes and creating user-friendly tools for non-specialized users. His work is particularly crucial in pandemic contexts and rapid diagnosis, enabling the referencing of pathogen sequences and identification of new pathogen-disease combinations.
Analysis of his recent publications reveals a strong focus on viral detection through metagenomic approaches, particularly for emerging pathogens. His research spans multiple vector systems including ticks, mosquitoes, and bats, with applications in public health surveillance and understanding viral evolution. The 2023 publication 'Virus Pop' demonstrates his innovative approach to expanding viral databases through protein sequence simulation, addressing the 'dark matter' problem in metagenomics.
Dr. Bigot actively contributes to the Bioinformatics program for PhD students at Institut Pasteur, having participated in courses from 2020 through 2024. His collaborative work spans multiple international research groups, reflecting the interdisciplinary nature of modern pathogen discovery research.
