Matthieu Chaldebas

PhD Candidate, Machine Learning for Human Genetics

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Professional Experience

Computational Biologist

St. Giles Laboratory of Human Genetics of Infectious Diseases

The Rockefeller University, New York & Imagine Institute, Paris | 2021 – Present

PhD Candidate

2022 – Present

  • Developed 5ULTRA, a machine-learning tool published in AJHG (2026) for predicting the impact of 5'UTR genetic variants on protein translation.
  • Selected to deliver a Platform Presentation at the ASHG 2025 Annual Meeting in Boston.
  • Applied 5ULTRA to discover novel genetic etiologies of infectious diseases and cancer-driving somatic mutations.

Bioinformatics Assistant

2021 – 2022

  • Operated and maintained bioinformatics pipelines for variant calling from over 26,000 WES/WGS datasets.
  • Conducted bulk and single-cell RNA-seq analyses for various projects within the lab.
  • Contributed to the development and validation of the AGAIN software (PNAS, 2023).

Data Scientist Intern

BioMérieux, Lyon, France | 6 Months – 2021

  • Optimized supervised machine learning models to increase predictive accuracy for antibiotic resistance.
  • Enhanced cross-validation to account for phylogenetic factors, improving model generalization.

Data Engineer Intern

CEA, Paris Saclay, France | 4 Months – 2019

  • Engineered data management pipelines for diverse biological datasets, enabling systematic phylogenetic analysis and 3D protein modeling.

Research Intern

Imagine Institute, Paris, France | 2 Months – 2018

  • Executed Western blot and quantitative RT-PCR assays to assess the effects of specific drugs on target gene expression.

Publications & Research Highlights

Selected for Platform Presentation — ASHG 2025
Published in AJHG (April 2026)

Genome-wide detection of human 5’UTR variants that impact protein translation

Chaldebas M, Ponsin K, Bohlen J, Conil C, Mourelatos H, Stenson PD, Cooper DN, Abel L, Casanova JL, Cobat A#, Zhang P#. (#Equal contribution)
The American Journal of Human Genetics (AJHG), 2026.

Research Highlight: Presented as a Platform Talk at the ASHG 2025 Annual Meeting. We developed 5ULTRA, a machine-learning framework to prioritize 5'UTR variants. By analyzing 28 million variants from gnomAD, we identified novel disease-causing mechanisms in cancer (ABI1, NRAS) and infectious diseases (TNF, RPSA).

Read at AJHG Try the Webserver Code on GitHub
Featured Publication

Genome-wide detection of human intronic AG-gain variants located between splicing branchpoints and canonical splice acceptor sites

Zhang P, Chaldebas M*, Ogishi M*, et al. (*Equal contributions)
PNAS, 2023.

My Contribution: As a second author, I contributed to the development and validation of the AGAIN software. My role involved performing data analysis on WES/WGS datasets, developing some key features, and validating variant impacts.

Read at PNAS Try the Webserver Code on GitHub

Core Bioinformatic Contributions to High-Impact Studies

As a bioinformatician at The Rockefeller University, I provided essential data analysis for numerous high-impact studies in human genetics and immunology.

Core Responsibilities:

WES/WGS Analysis
Executed germline variant calling, annotation, and filtering for cohort studies to identify candidate disease-causing variants.
RNA-seq Analysis
Performed differential gene expression, pathway analysis, and visualization to interpret functional consequences.
Custom Pipeline Development
Developed bioinformatics pipelines for project-specific analysis.

This work has contributed to publications in leading journals, including:

  • Nature (Arias et al., 2024; Chan et al., 2024)
  • Genome Medicine (Matuozzo et al., 2023; Conil et al., 2024)
  • Science Immunology (Ogishi et al., 2025; Yatim et al., 2026)
  • Journal of Experimental Medicine (Chan et al., 2024)
  • Immunity (Ogishi et al., 2024)
  • The Journal of Clinical Investigation (Arango-Franco et al., 2024)
222 Total Citations on Google Scholar

Technical Skills

Bioinformatics & Genomics

WES / WGS Analysis RNA-Seq (Bulk & scRNA) Proteomics Biostatistics Structural Biology

Programming & Data Science

Python R Machine Learning Bash PHP, HTML & CSS

Development & Tools

Version Control (Git) Cluster Computing Conda Docker/Singularity Snakemake

Education

PhD Candidate in Bioinformatics

Université Paris Cité, France | 2022 – 2026

M.Sc. in Biotechnology Engineering

Sup'Biotech, Paris, France | 2016 – 2021

Specialization in health data science.

Exchange semester at UCSD.