AIMC Topic: Mice, Transgenic

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Democratized image analytics by visual programming through integration of deep models and small-scale machine learning.

Nature communications Oct 7, 2019
Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we us...
Neural Networks, Computer Machine Learning Reproducibility of Results Animals Saccharomyces cerevisiae Green Fluorescent Proteins Mice, Transgenic Saccharomyces cerevisiae Proteins Dictyostelium Image Processing, Computer-Assisted Computational Biology Internet Life Cycle Stages Oocytes
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Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning.

Proceedings of the National Academy of Sciences of the United States of America Apr 11, 2019
Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies...
Microscopy, Fluorescence, Multiphoton Calcium Video Recording Mice, Transgenic Humans Animals Visual Cortex Deep Learning Image Processing, Computer-Assisted Mice Neurons
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Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models.

PloS one Mar 13, 2019
The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to ou...
Mice, Transgenic Cerebral Angiography Microscopy, Fluorescence, Multiphoton Imaging, Three-Dimensional Humans Mice Neural Networks, Computer Disease Models, Animal Animals Alzheimer Disease Cerebral Cortex
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Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.

American journal of physiology. Renal physiology Sep 26, 2018
Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identify...
Animals Male Diagnosis, Computer-Assisted Rats Disease Models, Animal Automation, Laboratory Phenotype Female Reproducibility of Results Kidney Glomerulus Microscopy Image Interpretation, Computer-Assisted Pattern Recognition, Automated Species Specificity Mice, Inbred C57BL Kidney Diseases Predictive Value of Tests Biopsy Workflow Mice, Transgenic Humans Machine Learning Software
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Organization of Neural Population Code in Mouse Visual System.

eNeuro Jul 17, 2018
The mammalian visual system consists of several anatomically distinct areas, layers, and cell types. To understand the role of these subpopulations in visual information processing, we analyzed neural signals recorded from excitatory neurons from var...
Support Vector Machine Signal Processing, Computer-Assisted Neurons Mice, Transgenic Visual Perception Animals Visual Cortex Mice
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A Novel Morphological Marker for the Analysis of Molecular Activities at the Single-cell Level.

Cell structure and function Jun 29, 2018
For more than a century, hematoxylin and eosin (H&E) staining has been the de facto standard for histological studies. Consequently, the legacy of histological knowledge is largely based on H&E staining. Due to the recent advent of multi-photon excit...
Fluorescence Resonance Energy Transfer MAP Kinase Signaling System Mice, Transgenic Machine Learning Mice, Inbred C57BL Animals Microscopy, Fluorescence Single-Cell Analysis Dogs Imaging, Three-Dimensional Madin Darby Canine Kidney Cells Biosensing Techniques
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Fully automated, deep learning segmentation of oxygen-induced retinopathy images.

JCI insight Dec 21, 2017
Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary...
Oxygen Observer Variation Deep Learning Algorithms Mice, Transgenic Image Processing, Computer-Assisted Female Retinal Neovascularization Microscopy, Confocal Animals Disease Models, Animal Mice, Inbred C57BL Male
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and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

The Journal of biological chemistry May 23, 2017
Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-s...
Artificial Intelligence Cells, Cultured Melanoma Reproducibility of Results Animals Computational Biology Cancer Vaccines Antigens, Neoplasm Immunogenicity, Vaccine Epitopes Vaccines, Synthetic Mice, Transgenic HLA-A2 Antigen Membrane Proteins Models, Immunological Protein Stability Humans Neoplasm Proteins Protein Refolding Expert Systems Mice, Knockout T-Lymphocytes, Cytotoxic Oligopeptides Peptide Fragments
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Contralateral artery enlargement predicts carotid plaque progression based on machine learning algorithm models in apoE mice.

Biomedical engineering online Dec 28, 2016
BACKGROUND: This study specifically focused on anatomical MRI characterization of the low shear stress-induced atherosclerotic plaque in mice. We used machine learning algorithms to analyze multiple correlation factors of plaque to generate predictiv...
Support Vector Machine Magnetic Resonance Imaging Mice, Inbred C57BL Decision Making Male Machine Learning Blood Flow Velocity Predictive Value of Tests Lipids Disease Progression Mice, Transgenic Ultrasonography, Doppler Algorithms Ultrasonography Apolipoproteins E Carotid Arteries Reproducibility of Results Mice Plaque, Atherosclerotic Sensitivity and Specificity Animals
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Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency.

Journal of neural engineering May 23, 2025
Brain computer interfaces (BCIs) require substantial cognitive flexibility to optimize control performance. Remarkably, learning this control is rapid, suggesting it might be mediated by neuroplasticity mechanisms operating on very short time scales....
Mice, Inbred C57BL Brain-Computer Interfaces Mice, Transgenic Optogenetics Male Mice Neuronal Plasticity Models, Neurological Learning Animals
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