2,211 results found
    1. Neuroscience

    Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

    Ruedeerat Keerativittayayut et al.
    Graph analysis revealed that spontaneous fluctuations of episodic-memory encoding performance associate with time-varying brain connectivity networks.
    1. Computational and Systems Biology
    2. Developmental Biology

    Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes

    Felix Y Zhou et al.
    A new computational framework provides a flexible and general approach for single and collective biological motion characterisation and phenotyping ideally suited for high-throughput timelapse screens.
    1. Computational and Systems Biology
    2. Neuroscience

    A simple generative model of the mouse mesoscale connectome

    Sid Henriksen et al.
    A realistic model of the connections between local populations of neurons in the adult mouse brain can be constructed based on just two biologically plausible rules.
    1. Computational and Systems Biology
    2. Neuroscience

    A connectome and analysis of the adult Drosophila central brain

    Louis K Scheffer et al.
    New reconstruction methods are used to create a publicly available dense reconstruction of the neurons and chemical synapses of central brain of Drosophila, with analysis of its graph properties.
    1. Computational and Systems Biology

    Science Forum: Wikidata as a knowledge graph for the life sciences

    Andra Waagmeester et al.
    Wikidata is continuously-updated resource that could improve the efficiency and accuracy of research in many areas of the life and biomedical sciences.
  1. Point of View: Correcting the bias against interdisciplinary research

    Ehud Shapiro
    When making decisions about funding and jobs the scientific community should recognise that most of the tools used to evaluate scientific excellence are biased in favour of established disciplines and against interdisciplinary research.

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