AI Medical Compendium Topic

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Mammals

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Profiling epigenetic age in single cells.

Nature aging
DNA methylation dynamics emerged as a promising biomarker of mammalian aging, with multivariate machine learning models ('epigenetic clocks') enabling measurement of biological age in bulk tissue samples. However, intrinsically sparse and binarized m...

MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex.

PLoS computational biology
Convolutional neural networks trained on object recognition derive inspiration from the neural architecture of the visual system in mammals, and have been used as models of the feedforward computation performed in the primate ventral stream. In contr...

Probing the rules of cell coordination in live tissues by interpretable machine learning based on graph neural networks.

PLoS computational biology
Robustness in developing and homeostatic tissues is supported by various types of spatiotemporal cell-to-cell interactions. Although live imaging and cell tracking are powerful in providing direct evidence of cell coordination rules, extracting and c...

Human-muscle-inspired single fibre actuator with reversible percolation.

Nature nanotechnology
Artificial muscles are indispensable components for next-generation robotics capable of mimicking sophisticated movements of living systems. However, an optimal combination of actuation parameters, including strain, stress, energy density and high me...

Combining mass spectrometry and machine learning to discover bioactive peptides.

Nature communications
Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the lit...

Structured random receptive fields enable informative sensory encodings.

PLoS computational biology
Brains must represent the outside world so that animals survive and thrive. In early sensory systems, neural populations have diverse receptive fields structured to detect important features in inputs, yet significant variability has been ignored in ...

Live fish learn to anticipate the movement of a fish-like robot.

Bioinspiration & biomimetics
The ability of an individual to predict the outcome of the actions of others and to change their own behavior adaptively is called anticipation. There are many examples from mammalian species-including humans-that show anticipatory abilities in a soc...

UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues.

Communications biology
Upcoming technologies enable routine collection of highly multiplexed (20-60 channel), subcellular resolution images of mammalian tissues for research and diagnosis. Extracting single cell data from such images requires accurate image segmentation, a...

A robotic model of hippocampal reverse replay for reinforcement learning.

Bioinspiration & biomimetics
Hippocampal reverse replay, a phenomenon in which recently active hippocampal cells reactivate in the reverse order, is thought to contribute to learning, particularly reinforcement learning (RL), in animals. Here, we present a novel computational mo...

Neuron tracing from light microscopy images: automation, deep learning and bench testing.

Bioinformatics (Oxford, England)
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey pape...