526 results found
    1. Physics of Living Systems

    Cellular organization in lab-evolved and extant multicellular species obeys a maximum entropy law

    Thomas C Day, Stephanie S Höhn ... Peter J Yunker
    The distributions of cellular neighborhood volumes in two very different multicellular species - snowflake yeast and Volvox carteri - are found to obey a common functional form arising from maximum entropy consideration, despite great differences in their cell division processes.
    1. Physics of Living Systems

    The ability to sense the environment is heterogeneously distributed in cell populations

    Andrew Goetz, Hoda Akl, Purushottam Dixit
    Information transduction capacity of mammalian cells is high and varies substantially from cell to cell.
    1. Neuroscience

    Asymmetric ON-OFF processing of visual motion cancels variability induced by the structure of natural scenes

    Juyue Chen, Holly B Mandel ... Damon A Clark
    The fruit fly estimates visual motion by incorporating ON-OFF asymmetric processing that only improves performance when stimuli have light-dark asymmetries matched to natural scenes.
    1. Computational and Systems Biology
    2. Neuroscience

    Interrogating theoretical models of neural computation with emergent property inference

    Sean R Bittner, Agostina Palmigiano ... John Cunningham
    Emergent property inference, a novel machine learning methodology, learns distributions of neural circuit model parameters that produce computational properties and provides novel scientific insight through the quantification of the rich parametric structure it captures.
    1. Neuroscience

    Cortical state transitions and stimulus response evolve along stiff and sloppy parameter dimensions, respectively

    Adrian Ponce-Alvarez, Gabriela Mochol ... Gustavo Deco
    Neurons differ in their impact on collective cortical activity, with sensitive neurons forming a stable topological core, implicated in cortical-state transitions, while peripheral insensitive neurons are more responsive to stimuli.
    1. Computational and Systems Biology
    2. Structural Biology and Molecular Biophysics

    Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding

    Xianqiang Sun, Sukrit Singh ... Gregory R Bowman
    Combining powerful simulation methods uncovers the structural and dynamical changes driving G protein activation in atomic detail, revealing the allosteric network that triggers GDP release and reconciling diverse experimental data.
    1. Immunology and Inflammation
    2. Physics of Living Systems

    Quantifying changes in the T cell receptor repertoire during thymic development

    Francesco Camaglia, Arie Ryvkin ... Nir Friedman
    Sequence signatures can be used to discriminate between selected and non-selected immune repertoires at different stages only at the collective population level but not at the level of single cells.
    1. Physics of Living Systems

    Glycan processing in the Golgi as optimal information coding that constrains cisternal number and enzyme specificity

    Alkesh Yadav, Quentin Vagne ... Madan Rao
    A mathematical model of glycosylation in the Golgi apparatus to investigate how the fidelity of synthesising a complex glycan distribution at the plasma membrane depends on parameters such as the number of Golgi cisternae or enzyme specificity.
    1. Computational and Systems Biology
    2. Neuroscience

    Graphical-model framework for automated annotation of cell identities in dense cellular images

    Shivesh Chaudhary, Sol Ah Lee ... Hang Lu
    Unbiased and automatic annotation using structured prediction framework with efficiently built data-driven atlases is more accurate than registration-based methods for cell identifications in dense images and enables fast whole-brain analysis.
    1. Neuroscience

    Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity

    Thijs L van der Plas, Jérôme Tubiana ... Georges Debrégeas
    A data-driven network model offers an interpretable and physiologically sound description of the whole-brain spontaneous neural activity of zebrafish larvae.

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