2,050 results found
    1. Cell Biology
    2. Computational and Systems Biology

    Active machine learning-driven experimentation to determine compound effects on protein patterns

    Armaghan W Naik et al.
    In an investigation into the effects of drugs on proteins, an active machine learning algorithm chose which sets of experiments to perform and was able to learn an accurate model of the effects after doing only a fraction of the experiments.
    1. Stem Cells and Regenerative Medicine

    Live cell-lineage tracing and machine learning reveal patterns of organ regeneration

    Oriol Viader-Llargués et al.
    A combination of live cell tracking, cell-lineage tracing and machine learning shows that injured sensory organs repair accurately regardless of the extent of damage.
    1. Neuroscience

    Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire

    Shuting Han et al.
    A novel automated behavior analysis method for Hydra identifies pre-defined and new behavior types, and reveals a stable behavior repertoire.
    1. Computational and Systems Biology
    2. Structural Biology and Molecular Biophysics

    Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning

    Yasuhiro Matsunaga, Yuji Sugita
    A general machine learning scheme for integrating time-series data from single-molecule experiments and molecular dynamics simulations is proposed and successfully demonstrated for the folding dynamics of the WW domain.
    1. Cancer Biology

    Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer

    Kevin M Elias et al.
    Application of machine learning to serum miRNA profiles generated through next generation sequencing identifies a biologically relevant miRNA signature which can be deployed as a qPCR test to assist the diagnosis of epithelial ovarian cancer.
    1. Plant Biology

    Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth

    Martial Sankar et al.
    Combining high-resolution imaging with automated image segmentation and supervised machine learning achieves accurate cellular feature extraction and automated cell type recognition in a large-scale developmental process.
    1. Computational and Systems Biology

    A computational interactome and functional annotation for the human proteome

    José Ignacio Garzón et al.
    A machine-learning approach is used to predict 1.35 million interactions for 85% of the human proteome.
    1. Computational and Systems Biology
    2. Ecology

    Data-driven identification of potential Zika virus vectors

    Michelle V Evans et al.
    Data-driven methods predict over 35 mosquitoes are potential vectors of Zika virus, suggesting a larger geographic area and a greater human population is at risk of infection.
    1. Computational and Systems Biology

    Systematic integration of biomedical knowledge prioritizes drugs for repurposing

    Daniel Scott Himmelstein et al.
    Project Rephetio combines data integration and systematic analysis to enable drug repurposing predictions on an unprecedented scale.
    1. Computational and Systems Biology
    2. Neuroscience

    Blood transcriptome based biomarkers for human circadian phase

    Emma E Laing et al.
    An unbiased modelling approach shows that only a few blood transcriptome samples are required to accurately assess the human circadian melatonin phase, even during altered sleep schedules.

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