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Showing 1–7 of 7 results
Advanced filters: Author: Pau Badia-i-Mompel Clear advanced filters

  • Lerma-Martin et al. generated a paired single-nucleus RNA sequencing and spatial transcriptomics dataset from subcortical multiple sclerosis lesions, identifying spatial niches and key cell interactions driving inflammation and disease progression at the lesion rim.

    • Celia Lerma-Martin
    • Pau Badia-i-Mompel
    • Lucas Schirmer
    ResearchOpen Access
    Nature Neuroscience
    Volume: 27, P: 2354-2365

  • Small molecules bioactivity descriptors are enriched representations of compounds, reaching beyond chemical structures and capturing their known biological properties. Here the authors present a collection of deep neural networks able to infer bioactivity signatures for any compound of interest, even when little or no experimental information is available for them.

    • Martino Bertoni
    • Miquel Duran-Frigola
    • Patrick Aloy
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-13

  • A spatial transcriptomics and single-cell multiomics study performed on mouse brain tissue. Here, authors show region-specific spaceflight-induced alterations in processes of neurogenesis, synaptogenesis and synaptic transmission.

    • Yuvarani Masarapu
    • Egle Cekanaviciute
    • Stefania Giacomello
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-14

  • Dimitrov et al. present LIANA+, a framework that unifies and extends approaches to study inter- and intracellular signalling from diverse mediators, captured from single-cell, spatially resolved and multi-omics data.

    • Daniel Dimitrov
    • Philipp Sven Lars Schäfer
    • Julio Saez-Rodriguez
    ResearchOpen Access
    Nature Cell Biology
    Volume: 26, P: 1613-1622

  • Wanner et al. demonstrate SARS-CoV-2 liver tropism and identify transcriptional and proteomic profiles of SARS-CoV-2 liver samples that show similarities to previously characterized hepatotropic viruses.

    • Nicola Wanner
    • Geoffroy Andrieux
    • Tobias B. Huber
    ResearchOpen Access
    Nature Metabolism
    Volume: 4, P: 310-319

  • Regulatory circuits of gene expression can be represented as gene regulatory networks (GRNs) that are useful to understand cellular identity and disease. Here, the authors review the computational methods used to infer GRNs — in particular from single-cell multi-omics data — as well as the biological insights that they can provide, and methods for their downstream analysis and experimental assessment.

    • Pau Badia-i-Mompel
    • Lorna Wessels
    • Julio Saez-Rodriguez
    Reviews
    Nature Reviews Genetics
    Volume: 24, P: 739-754

  • Practitioners in the field of single-cell omics are now faced with diverse options for analytical tools to process and integrate data from various molecular modalities. In an Expert Recommendation article, the authors provide guidance on robust single-cell data analysis, including choices of best-performing tools from benchmarking studies.

    • Lukas Heumos
    • Anna C. Schaar
    • Fabian J. Theis
    Reviews
    Nature Reviews Genetics
    Volume: 24, P: 550-572