Laura Cantini is tenured researcher in CNRS, chair in the Paris Institute of AI (PRAIRIE) and G5 junior group leader heading the Machine Learning for Integrative Genomics group. Mathematician by training, Laura works at the interphase of machine learning/AI and genomics. Due to the advent of single-cell high-throughput technologies, multiple large-scale quantitative measurements, a.k.a. omics, can be accessed for the same cells. Laura’s lab focuses on the development of machine learning and AI methods able to co-analyze the numerous available single-cell omics data and translate them into actionable biological knowledge. The work of Laura Cantini has been recognized by multiple grants and awards, including the ERC StG, the Sanofi iTech award and the bronze medal of CNRS.
Courses
Artificial Intelligence (AI) in Neurosciences hands-on workshop
This workshop provides training in modelling and model-driven analysis of neuroscience experimental data. We will cover fundamental principles of neural data analysis, behaviour video data and show recent progress in these approaches. The workshop […]
Artificial Intelligence (AI) in Structural Biology hands-on workshop
Part 1. Critical use of AI for 3D structure prediction Instructors: Benjamin Bardiaux (Permanent researcher in the Bacterial Transmembrane Systems Unit at Institut Pasteur) & Ludovic Sauguet (Research director in the Architecture & Dynamics […]
Artificial Intelligence (AI) in Genomics hands-on workshop
Part 1. Fine-tuning biological LLMs for functional classification Intructor: Ernest Mordret (postdoctoral researcher at the Institut Pasteur) Large Language Models (LLMs) are revolutionizing biology! They capture intricate patterns within DNA and protein sequences through […]
AI for Life Sciences Theoretical Workshop for Pasteur PhD students
In 2024, at the request of Yasmine Belkaid, General Director of the Institut Pasteur, a Theoretical Workshop is offered to all Pasteur PhD candidates to strengthen research capabilities in areas such as image processing, […]
Transversal Projects
Projects
CV
Academic positions:
- From 2023 : G5 junior group leader, Institut Pasteur, Paris
- From 2021: Chair position, Institut Prairie, Paris
- 2019: Visiting researcher, MIT CSAIL department, Cambridge, US (head: Manolis Kellis)
- From 2018: CNRS tenured researcher (Chargé de Recherche)
Awards:
- 2024: CNRS bronze medal
- 2022: prix Paoletti
- 2020: Sanofi iTech Awards
- 2018: L’Oreal-UNESCO Fellowship for women in science
Grants:
- 2024: ERC StG Multiview-CELL
- 2024: PEPR CELL-ID
- 2024: PEPR Santé Numerique
- 2022: ITMO-MIIC APL-EpiNet
- 2020: ANR JCJC scMOmix
- 2016-2018: Postdoctoral fellow, Institut Curie, Paris (head: Emmanuel Barillot)
- 2014-2015: Visiting Ph.D student, Aalto university, Helsinki, Finland (head: Santo Fortunato)
- 2013-2015: Ph.D student, University of Turin, Italy (head: Michele Caselle, Enzo Medico)
Publications
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2025scPRINT: pre-training on 50 million cells allows robust gene network predictions., Nat Commun 2025 Apr; 16(1): 3607.
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2025IL-23 tunes inflammatory functions of human mucosal-associated invariant T cells., iScience 2025 Feb; 28(2): 111898.
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2024scConfluence: single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features., Nat Commun 2024 Sep; 15(1): 7762.
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2024Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS., Bioinformatics 2024 Mar; (): .
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2023Paired single-cell multi-omics data integration with Mowgli., Nat Commun 2023 Nov; 14(1): 7711.
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2022Optimal Transport improves cell-cell similarity inference in single-cell omics data., Bioinformatics 2022 Feb; 38(8): 2169-77.
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2021Benchmarking joint multi-omics dimensionality reduction approaches for the study of cancer., Nat Commun 2021 Jan; 12(1): 124.
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2021Evaluating the Reproducibility of Single-Cell Gene Regulatory Network Inference Algorithms., Front Genet 2021 ; 12(): 617282.
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2020An Integrated Analysis of miRNA and Gene Expression Changes in Response to an Obesogenic Diet to Explore the Impact of Transgenerational Supplementation with Omega 3 Fatty Acids., Nutrients 2020 Dec; 12(12): .
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2020Collective intelligence defines biological functions in Wikipedia as communities in the hidden protein connection network., PLoS Comput Biol 2020 Feb; 16(2): e1007652.
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