1,514 results found
    1. Computational and Systems Biology
    2. Developmental Biology

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

    Luciano Marcon et al.
    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. Cell Biology
    2. Computational and Systems Biology

    Signaling pathways as linear transmitters

    Harry Nunns, Lea Goentoro
    Mathematical and experimental analyses suggest that despite their complex architectures, multiple metazoan signaling pathways act in physiological contexts as linear signal transmitters.
    1. Computational and Systems Biology
    2. Developmental Biology

    Systems biology derived source-sink mechanism of BMP gradient formation

    Joseph Zinski et al.
    Embryo-wide quantitative analysis of BMP signaling in zebrafish embryos, combined with a mathematical model-based computational screen, challenges the prevailing model of an antagonist counter-gradient shaping the gastrula BMP morphogen gradient and supports an antagonist sink with BMP diffusion mechanism.
    1. Computational and Systems Biology
    2. Developmental Biology

    Stochasticity in the miR-9/Hes1 oscillatory network can account for clonal heterogeneity in the timing of differentiation

    Nick E Phillips et al.
    Stochasticity introduced computationally into a gene expression oscillator creates heterogeneity in the time of differentiation of identical cells and offers robustness to the progenitor state and the outcome of cell division.
    1. Computational and Systems Biology
    2. Neuroscience

    Training deep neural density estimators to identify mechanistic models of neural dynamics

    Pedro J Gonçalves et al.
    Deep neural networks can be trained to automatically find mechanistic models which quantitatively agree with experimental data, providing new opportunities for building and visualizing interpretable models of neural dynamics.
    1. Evolutionary Biology
    2. Physics of Living Systems

    Global epistasis emerges from a generic model of a complex trait

    Gautam Reddy, Michael M Desai
    Predictable patterns of fitness evolution observed in microbial evolution experiments can emerge generically as a consequence of widespread epistatic interactions between mutations.
    1. Epidemiology and Global Health

    Evaluating distributional regression strategies for modelling self-reported sexual age-mixing

    Timothy M Wolock et al.
    Integrating the sinh-arcsinh distribution into a distributional regression framework allows us to produce precise, local estimates of sexual age-mixing, facilitating more accurate modelling of sexually transmitted disease dynamics.
    1. Neuroscience

    Synaptic learning rules for sequence learning

    Eric Torsten Reifenstein et al.
    Through mathematical analysis and computer simulations, the neuronal underpinnings of feasible models of sequence learning are delineated.
    1. Computational and Systems Biology
    2. Chromosomes and Gene Expression

    Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism

    Iain G Johnston et al.
    New modelling, statistics, and experiments show that cellular populations of mitochondrial DNA (mtDNA) evolve during development according to solvable stochastic dynamics involving binomial partitioning and random turnover, facilitating a predictive and quantitative theory of the mtDNA bottleneck.
    1. Computational and Systems Biology
    2. Developmental Biology

    Control of tissue development and cell diversity by cell cycle-dependent transcriptional filtering

    Maria Abou Chakra et al.
    A mathematical model predicts that cell cycle duration acts as a transcriptional filter and directly affects cell diversity in early eukaryotic development.

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