AIMC Topic: Mice

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Using Deep Learning to Extrapolate Protein Expression Measurements.

Proteomics Oct 16, 2020
Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for i...
Proteomics Mass Spectrometry Proteins Molecular Sequence Annotation Animals Deep Learning Mice
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Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires.

PLoS computational biology Oct 15, 2020
Animals produce vocalizations that range in complexity from a single repeated call to hundreds of unique vocal elements patterned in sequences unfolding over hours. Characterizing complex vocalizations can require considerable effort and a deep intui...
Cluster Analysis Databases, Factual Unsupervised Machine Learning Sound Spectrography Animals Vocalization, Animal Humans Mice Songbirds Chiroptera Computational Biology Algorithms Voice
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Spage2vec: Unsupervised representation of localized spatial gene expression signatures.

The FEBS journal Oct 11, 2020
Investigations of spatial cellular composition of tissue architectures revealed by multiplexed in situ RNA detection often rely on inaccurate cell segmentation or prior biological knowledge from complementary single-cell sequencing experiments. Here,...
Humans Cell Line Neural Networks, Computer Animals Internet Gene Expression Profiling Somatosensory Cortex Computational Biology Gene Ontology Transcriptome Cluster Analysis CA1 Region, Hippocampal Gene Regulatory Networks Fibroblasts Mice
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Data mining of human plasma proteins generates a multitude of highly predictive aging clocks that reflect different aspects of aging.

Aging cell Oct 8, 2020
We previously identified 529 proteins that had been reported by multiple different studies to change their expression level with age in human plasma. In the present study, we measured the q-value and age coefficient of these proteins in a plasma prot...
Aged Young Adult Adult Animals Humans Machine Learning Disease Models, Animal Blood Proteins Data Mining Longevity Aging Middle Aged Adolescent Mice
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Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination.

NeuroImage Oct 6, 2020
The intra-axonal water exchange time (τ), a parameter associated with axonal permeability, could be an important biomarker for understanding and treating demyelinating pathologies such as Multiple Sclerosis. Diffusion-Weighted MRI (DW-MRI) is sensiti...
Cuprizone Microscopy, Electron Monte Carlo Method White Matter Mice Demyelinating Diseases Disease Models, Animal Diffusion Magnetic Resonance Imaging Computer Simulation Permeability Corpus Callosum Animals Axons Machine Learning Monoamine Oxidase Inhibitors Image Processing, Computer-Assisted
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Modeling a population of retinal ganglion cells with restricted Boltzmann machines.

Scientific reports Oct 6, 2020
The retina is a complex circuit of the central nervous system whose aim is to encode visual stimuli prior the higher order processing performed in the visual cortex. Due to the importance of its role, modeling the retina to advance in interpreting it...
Photic Stimulation Animals Neural Networks, Computer Mice Retina Machine Learning Retinal Ganglion Cells Algorithms
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Lignin-Incorporated Nanogel Serving As an Antioxidant Biomaterial for Wound Healing.

ACS applied bio materials Oct 1, 2020
Oxidative phosphorylation is an important biological process in the body to produce energy, during which oxygen free radicals are generated as byproduct. Excessive oxygen free radicals cause cell death and reduce the rate of tissue regeneration and h...
Micelles Particle Size Skin Nanogels Burns Rheology Antioxidants Polyethylene Glycols Wound Healing Animals Lignin Disease Models, Animal Male Hydrogels Mice, Inbred BALB C Mice Biocompatible Materials
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Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution.

Respiratory physiology & neurobiology Sep 30, 2020
Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardi...
Machine Learning Animals Mice Age Factors Respiratory System Mice, Inbred C57BL Plethysmography Tidal Volume Animals, Newborn Respiratory Physiological Phenomena
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Deep learning of immune cell differentiation.

Proceedings of the National Academy of Sciences of the United States of America Sep 25, 2020
Although we know many sequence-specific transcription factors (TFs), how the DNA sequence of cis-regulatory elements is decoded and orchestrated on the genome scale to determine immune cell differentiation is beyond our grasp. Leveraging a granular a...
Animals Deep Learning Mice Transcription Factors Databases, Genetic Gene Expression Regulation Hematopoiesis Regulatory Sequences, Nucleic Acid Humans Chromatin
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Comparing biological and artificial vision systems: Network measures of functional connectivity.

Neuroscience letters Sep 24, 2020
Advances in Deep Convolutional Neural Networks (DCNN) provide new opportunities for computational neuroscience to pose novel questions regarding the function of biological visual systems. Some attempts have been made to utilize advances in machine le...
Neurons Visual Cortex Recognition, Psychology Mice Models, Neurological Data Interpretation, Statistical Neural Networks, Computer Animals
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