• About me
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    • Invited speaker at Astrazeneca, Computational Biology Seminar
    • Principles of multi-omics data integration (Cambridge AI Club for Biomedicine)
    • Invited speaker at Harvard Medical School, Centre for Computational Biology Seminar Series
    • Poster presentation at the Single Cell Genomics 2022 conference
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    • Data integration techniuqes for the 10x Chromium single-cell Multiome technology (10x Genomics Webinar Series)
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    • Poster presentation at the conference 'Biology of Genomes'
    • Selected speaker at the Single Cell Genomics conference
    • Selected speaker at the Mathematical and Statistical Aspects of Molecular Biology conference
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    • Selected talk at the conference 'From Single- to Multiomics: Applications and Challenges'
    • Selected talk at the 4th Bioinformatics and Genomics Symposium
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    • Gene regulatory network inference in the era of single-cell multi-omics
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  • Teaching
    • MOFA workshop (VIB Training, 2018-2022)
    • Demonstrator at the course 'Integrative analysis of multi-omics data' (EMBL, 2022)
    • Instructor at the IARC-SIB course: 'Multivariate analysis for -omics data integration: principles and applications'
    • Adjunct professor, MSc Bioinformatics at Universitat Pompeu Fabra (2020-2022)
    • Adjunct professor, MSc Bioinformatics at Universitat Pompeu Fabra
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    • Demonstrator at the course 'Systems biology: From large datasets to biological insight' (EMBL-EBI)
    • Demonstrator at the course 'Introduction to multiomics data integration' (EMBL-EBI, 2018 and 2019)
    • Supervisor at the BSc course 'Mathematical Biology' at Cambridge University (2017-2020)
    • Teaching assistant, MSc Bioinformatics at Copenhagen University (2015-2016)
  • Publications
    • Decoding gene regulation in the mouse embryo using single-cell multi-omics
    • Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO
    • Inter-gastruloid heterogeneity revealed by single cell transcriptomics time course: implications for organoid based perturbation studies
    • Single-cell multi-omics profiling links dynamic DNA methylation to cell fate decisions during mouse early organogenesis
    • Integrative Transkingdom Analysis of the Gut Microbiome in Antibiotic Perturbation and Critical Illness
    • scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution
    • MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
    • Multi-omics profiling of mouse gastrulation at single-cell resolution
    • Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets
    • scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells
  • Supervision
    • Brendan Terry (2021-2022): Multi-modal CRISPR screenings at single-cell resolution
    • Bart Theeuwes (2021 - 2022): Deciphering gene regulatory network control of embryonic haematopoiesis from single-cell multi-modal data
    • Gavin Li (2021 - 2022): modelling gene regulatory networks from single-cell multi-modal data
    • Yonatan Deloro (2018): Factor Analysis Models for Genomics data

Poster presentation at the Single Cell Genomics 2017 conference

Oct 16, 2017 · 0 min read
Slides
Last updated on Oct 16, 2017
Ricard Argelaguet
Authors
Ricard Argelaguet
Senior Research Scientist
← Selected speaker at the Mathematical and Statistical Aspects of Molecular Biology conference Mar 19, 2018
Selected talk at the conference 'From Single- to Multiomics: Applications and Challenges' Sep 26, 2017 →

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