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Showing 1–7 of 7 results
Advanced filters: Author: Lorenzo Bonaguro Clear advanced filters

  • High-dimensional cytometry is a powerful technology for studying single-cell phenotypes in complex biological systems. Here, the authors develop cyCONDOR, a computational framework for high-dimensional cytometry data analysis, covering a comprehensive suite of features in an easy-to-use format.

    • Charlotte Kröger
    • Sophie Müller
    • Lorenzo Bonaguro
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-16

  • Swarm Learning is a decentralized machine learning approach that outperforms classifiers developed at individual sites for COVID-19 and other diseases while preserving confidentiality and privacy.

    • Stefanie Warnat-Herresthal
    • Hartmut Schultze
    • Joachim L. Schultze
    ResearchOpen Access
    Nature
    Volume: 594, P: 265-270

  • Synthetic embryo models have arisen as an approach to probe early development in vitro, facilitating the study of difficult to access stages. Here the authors present a simple system for generating embryo-like structures that resemble peri-implantation mouse embryos.

    • Jan Langkabel
    • Arik Horne
    • Hubert Schorle
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-18

  • Within a human cohort, wide variation can occur with constitutively expressed proteins. Aschenbrenner and colleagues found that individuals with lower CRELD1 expression have decreased frequencies of naive CD4+ T cells. Mice with conditional Creld1 deficiency also exhibit a phenotype associated with immunological aging.

    • Lorenzo Bonaguro
    • Maren Köhne
    • Anna C. Aschenbrenner
    Research
    Nature Immunology
    Volume: 21, P: 1517-1527

  • The explosion of single-cell and systems approaches in immunology risks leaving the uninitiated behind. This guide to systems immunology is designed for immunologists who want an introduction to the area.

    • Lorenzo Bonaguro
    • Jonas Schulte-Schrepping
    • Joachim L. Schultze
    Reviews
    Nature Immunology
    Volume: 23, P: 1412-1423