AIMC Topic: Mice

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A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis.

Journal of visualized experiments : JoVE Feb 6, 2020
Understanding behavior is the first step to truly understanding neural mechanisms in the brain that drive it. Traditional behavioral analysis methods often do not capture the richness inherent to the natural behavior. Here, we provide detailed step-b...
Neural Networks, Computer Animals Deep Learning User-Computer Interface Humans Behavior, Animal Computer Graphics Behavior Imaging, Three-Dimensional Interpersonal Relations Mice Video Recording Automation
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A Comparison between Mouse, , and Robot Odor Plume Navigation Reveals Advantages of Mouse Odor Tracking.

eNeuro Feb 4, 2020
Localization of odors is essential to animal survival, and thus animals are adept at odor navigation. In natural conditions animals encounter odor sources in which odor is carried by air flow varying in complexity. We sought to identify potential min...
Robotics Odorants Smell Movement Algorithms Computer Simulation Animals Mice
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Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method.

NeuroImage Jan 29, 2020
Diffusion Magnetic Resonance Imaging (dMRI) has shown great potential in probing tissue microstructure and structural connectivity in the brain but is often limited by the lengthy scan time needed to sample the diffusion profile by acquiring multiple...
Principal Component Analysis Animals Machine Learning Nerve Net Image Processing, Computer-Assisted Diffusion Magnetic Resonance Imaging Brain Mice Female Mice, Inbred C57BL
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A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.

Scientific reports Jan 22, 2020
High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncover...
Mice Genomics Computational Biology Proteomics Metabolomics Cell Line Cell Survival Autophagy Humans Machine Learning Animals Gene Regulatory Networks Adenosine Triphosphate Huntington Disease
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MMPdb and MitoPredictor: Tools for facilitating comparative analysis of animal mitochondrial proteomes.

Mitochondrion Jan 20, 2020
Data on experimentally-characterized animal mitochondrial proteomes (mt-proteomes) are limited to a few model organisms and are scattered across multiple databases, impeding a comparative analysis. We developed two resources to address these problems...
Acanthamoeba castellanii Humans Drosophila melanogaster Caenorhabditis elegans Databases, Protein Mitochondrial Proteins Machine Learning Mitochondria Energy Metabolism Animals Saccharomyces cerevisiae Mice Proteome
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Prediction of peptide binding to MHC using machine learning with sequence and structure-based feature sets.

Biochimica et biophysica acta. General subjects Jan 16, 2020
Selecting peptides that bind strongly to the major histocompatibility complex (MHC) for inclusion in a vaccine has therapeutic potential for infections and tumors. Machine learning models trained on sequence data exist for peptide:MHC (p:MHC) binding...
Alleles Histocompatibility Antigens Class I Animals Amino Acid Sequence Protein Conformation Peptides Machine Learning Algorithms Protein Binding Mice
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An efficient analytical reduction of detailed nonlinear neuron models.

Nature communications Jan 15, 2020
Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of ...
Pyramidal Cells Dendrites N-Methylaspartate alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid Calcium Nonlinear Dynamics Synapses gamma-Aminobutyric Acid Mice Models, Neurological Neurons Neural Networks, Computer Algorithms Animals Spatio-Temporal Analysis
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Machine learning derived input-function in a dynamic F-FDG PET study of mice.

Biomedical physics & engineering express Jan 13, 2020
Tracer kinetic modelling, based on dynamic F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. O...
Radiopharmaceuticals Positron-Emission Tomography Image Interpretation, Computer-Assisted Female Machine Learning Arteries Fluorodeoxyglucose F18 Animals Algorithms Computer Simulation Mice Mice, Inbred BALB C
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Label-Free Tomographic Imaging of Lipid Droplets in Foam Cells for Machine-Learning-Assisted Therapeutic Evaluation of Targeted Nanodrugs.

ACS nano Jan 10, 2020
Lipid droplet (LD) accumulation, a key feature of foam cells, constitutes an attractive target for therapeutic intervention in atherosclerosis. However, despite advances in cellular imaging techniques, current noninvasive and quantitative methods hav...
Mice Foam Cells Machine Learning Nanoparticles Tomography, Optical Cells, Cultured Particle Size Lipid Droplets Animals Atherosclerosis Imaging, Three-Dimensional RAW 264.7 Cells Surface Properties Thiazolidinediones Pyrimidines
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In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics.

Nature communications Jan 9, 2020
Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent acquisition (DDA) experiments are required prior to DIA ...
Humans Computer Simulation Animals Peptides Peptide Library Computational Biology Proteomics Proteome Deep Learning Data Science Cell Line, Tumor Mice Mass Spectrometry Databases, Protein HeLa Cells Serum
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