Ricard Argelaguet

Senior Research Scientist

About Me

I am a computational biologist motivated by the applications of machine learning and artifical intelligence to the field of biology.

I did my PhD in the groups of John Marioni (EMBL-EBI, now at Genentech) and Oliver Stegle (EMBL & DKFZ), followed by a short postdoctoral stay in the group of Wolf Reik at the Babraham Institute. I developed methods for single-cell and multi-omics data integration, the most popular one being MOFA. I also worked on generating data resources in the context of embryonic development. Some examples are the single-cell multi-modal atlases of mouse gastrulation and early organogenesis.

Currently, I am working as a Senior Scientist at Altos Labs in the AI/ML team led by Thore Graepel, where I work on modelling gene perturbation screenings to characterise the regulatory networks that underlie cellular rejuvenation programming.

I am a strong advocate of open and reproducible science. If you are interested in my work please check my GitHub page, which includes code to reproduce many of the results from our publications.

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Interests

Data analysis
Computational Biology
Multi-omics data integration
Single-cell omics
Machine Learning

Education

PhD in Statistical Genomics
EMBL-EBI & University of Cambridge
MSc in Bioinformatics
Copenhagen University (Copenhagen, Denmark)
BSc in Human Biology
Universitat Pompeu Fabra (Barcelona, Catalonia, Spain)

Selected publications

Ricard Argelaguet, Tim Lohoff, Jingyu Gavin Li, Asif Nakhuda, Deborah Drage, Felix Krueger, Lars Velten, Stephen J. Clark, Wolf Reik (2022). Decoding gene regulation in the mouse embryo using single-cell multi-omics. bioRxiv.

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Britta Velten, Jana M. Braunger, Ricard Argelaguet, Damien Arnol, Jakob Wirbel, Danila Bredikhin, Georg Zeller, Oliver Stegle (2022). Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO. Nature Methods.

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Leah U. Rosen, L. Carine Stapel, Ricard Argelaguet, Charlie George Barker, Andrian Yang, Wolf Reik, John C. Marioni (2022). Inter-gastruloid heterogeneity revealed by single cell transcriptomics time course: implications for organoid based perturbation studies. bioRxiv.

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Stephen J. Clark, Ricard Argelaguet, Tim Lohoff, Felix Krueger, Deborah Drage, Berthold Göttgens, John C. Marioni, Jennifer Nichols, Wolf Reik (2022). Single-cell multi-omics profiling links dynamic DNA methylation to cell fate decisions during mouse early organogenesis. Genome Biology.

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Bastiaan W. Haak, Ricard Argelaguet, Cormac M. Kinsella, Robert F. J. Kullberg, Jacqueline M. Lankelma, Martin Deijs, Michelle Klein, Maarten F. Jebbink, Floor Hugenholtz, Sarantos Kostidis, Martin Giera, Theodorus B. M. Hakvoort, Wouter J. De Jonge, Marcus J. Schultz, Tom Van Gool, Tom Van Der Poll, Willem M. De Vos, Lia M. Van Der Hoek, W. Joost Wiersinga (2021). Integrative Transkingdom Analysis of the Gut Microbiome in Antibiotic Perturbation and Critical Illness. mSystems.

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Reviews

Pau Badia-I-Mompel, Lorna Wessels, Sophia Müller-Dott, Rémi Trimbour, Ricardo O. Ramirez Flores, Ricard Argelaguet, Julio Saez-Rodriguez (2023). Gene regulatory network inference in the era of single-cell multi-omics. Nature Reviews Genetics.

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Ricard Argelaguet, Anna S E Cuomo, Oliver Stegle, John C Marioni (2021). Computational principles and challenges in single-cell data integration. Nature Biotechnology.

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Talks

(2024). Invited speaker at Astrazeneca, Computational Biology Seminar.

Slides

(2024). Principles of multi-omics data integration (Cambridge AI Club for Biomedicine) .

Slides

(2023). Invited speaker at Harvard Medical School, Centre for Computational Biology Seminar Series.

Slides

(2022). Poster presentation at the Single Cell Genomics 2022 conference.

Slides