1,352 results found
    1. Computational and Systems Biology

    Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination

    Fuqing Wu, Ri-Qi Su ... Xiao Wang
    A synthetic quadrastable gene network provides a synthetic biology framework to study cell fate determination.
    1. Computational and Systems Biology

    Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics

    Mayank Baranwal, Ryan L Clark ... Ophelia S Venturelli
    Recurrent neural network models enable prediction and design of health-relevant metabolite dynamics in synthetic human gut communities.
    1. Computational and Systems Biology
    2. Physics of Living Systems

    Phenotypic states become increasingly sensitive to perturbations near a bifurcation in a synthetic gene network

    Kevin Axelrod, Alvaro Sanchez, Jeff Gore
    Perturbations in the extracellular environment drive transitions from a highly stable memory state to an alternative phenotype in microorganisms.
    1. Biochemistry and Chemical Biology
    2. Computational and Systems Biology

    Rapid cell-free forward engineering of novel genetic ring oscillators

    Henrike Niederholtmeyer, Zachary Z Sun ... Sebastian J Maerkl
    Rapid forward engineering can be accomplished using cell-free systems, as demonstrated by the implementation and characterization of novel genetic oscillators in a cell-free system and their consequent transfer to cells.
    1. Computational and Systems Biology
    2. Developmental Biology

    High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

    Luciano Marcon, Xavier Diego ... Patrick Müller
    Realistic reaction-diffusion signaling networks that include cell-autonomous factors can robustly form self-organizing spatial patterns for any combination of diffusion coefficients without requiring differential diffusivity.
    1. Neuroscience
    2. Physics of Living Systems

    Fast deep neural correspondence for tracking and identifying neurons in C. elegans using semi-synthetic training

    Xinwei Yu, Matthew S Creamer ... Andrew M Leifer
    A deep neural network trained on semi-synthetic data learns to quickly track and identify neurons in Caenorhabditis elegans.
    1. Computational and Systems Biology
    2. Epidemiology and Global Health

    Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus

    Sen Pei, Flaviano Morone ... Jeffrey L Shaman
    The asymptomatic colonization and importation of methicillin-resistant Staphylococcus aureus (MRSA) in hospital settings can be inferred from observed cases using combined model-inference methods and used to inform improved interventions.
    1. Cell Biology
    2. Neuroscience

    Speed and segmentation control mechanisms characterized in rhythmically-active circuits created from spinal neurons produced from genetically-tagged embryonic stem cells

    Matthew J Sternfeld, Christopher A Hinckley ... Samuel L Pfaff
    Stem cell derived ventral-spinal cord excitatory neurons self-assemble into a rhythmically bursting neural network whose speed and intercellular coordination are both instructively modulated by cell-type specific interactions with inhibitory neurons.
    1. Neuroscience

    Gated recurrence enables simple and accurate sequence prediction in stochastic, changing, and structured environments

    Cédric Foucault, Florent Meyniel
    Small gated recurrent neural networks can dynamically adapt to inferred changes in the environment, represent and use the precision of their estimate to weight their updates, and leverage the environment's latent hierarchical structure, like the Bayesian agent and the brain.
    1. Chromosomes and Gene Expression
    2. Computational and Systems Biology

    Local genetic context shapes the function of a gene regulatory network

    Anna Nagy-Staron, Kathrin Tomasek ... Calin C Guet
    The phenotype of a gene regulatory network depends both qualitatively and quantitatively on the local genetic context of its individual components and cannot necessarily be predicted solely from network's topology.

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