AIMC Topic: Mice

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Microscope-Based Automated Quantification of Liver Fibrosis in Mice Using a Deep Learning Algorithm.

Toxicologic pathology Mar 26, 2021
In preclinical studies that involve animal models for hepatic fibrosis, accurate quantification of the fibrosis is of utmost importance. The use of digital image analysis based on deep learning artificial intelligence (AI) algorithms can facilitate a...
Microscopy Deep Learning Mice Artificial Intelligence Liver Cirrhosis Algorithms Animals
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EDLMFC: an ensemble deep learning framework with multi-scale features combination for ncRNA-protein interaction prediction.

BMC bioinformatics Mar 19, 2021
BACKGROUND: Non-coding RNA (ncRNA) and protein interactions play essential roles in various physiological and pathological processes. The experimental methods used for predicting ncRNA-protein interactions are time-consuming and labor-intensive. Ther...
Software Animals Deep Learning Mice Neural Networks, Computer Computational Biology RNA, Untranslated
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Action detection using a neural network elucidates the genetics of mouse grooming behavior.

eLife Mar 17, 2021
Automated detection of complex animal behaviors remains a challenging problem in neuroscience, particularly for behaviors that consist of disparate sequential motions. Grooming is a prototypical stereotyped behavior that is often used as an endopheno...
Neural Networks, Computer Behavior, Animal Machine Learning Grooming Male Female Ethology Mice Animals Mice, Inbred C57BL
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JSOM: Jointly-evolving self-organizing maps for alignment of biological datasets and identification of related clusters.

PLoS computational biology Mar 16, 2021
With the rapid advances of various single-cell technologies, an increasing number of single-cell datasets are being generated, and the computational tools for aligning the datasets which make subsequent integration or meta-analysis possible have beco...
Humans Algorithms Databases, Factual Computational Biology Sequence Analysis, RNA Animals Mice Cluster Analysis Unsupervised Machine Learning Flow Cytometry
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Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations.

Nature biomedical engineering Mar 11, 2021
The de novo design of antimicrobial therapeutics involves the exploration of a vast chemical repertoire to find compounds with broad-spectrum potency and low toxicity. Here, we report an efficient computational method for the generation of antimicrob...
Molecular Dynamics Simulation Amino Acid Sequence Pseudomonas aeruginosa Acinetobacter baumannii Animals Mice, Inbred BALB C Anti-Bacterial Agents Drug Design Mice Klebsiella Infections Antimicrobial Cationic Peptides Drug Resistance, Bacterial Drug Discovery Deep Learning Klebsiella pneumoniae Escherichia coli Structure-Activity Relationship Female Staphylococcus aureus Microbial Sensitivity Tests
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DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires.

Nature communications Mar 11, 2021
Deep learning algorithms have been utilized to achieve enhanced performance in pattern-recognition tasks. The ability to learn complex patterns in data has tremendous implications in immunogenomics. T-cell receptor (TCR) sequencing assesses the diver...
Deep Learning RNA-Seq Receptors, Antigen, T-Cell Algorithms Animals T-Lymphocytes High-Throughput Nucleotide Sequencing Mice Databases, Genetic Amino Acid Sequence Humans Neural Networks, Computer
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Deep learning based neuronal soma detection and counting for Alzheimer's disease analysis.

Computer methods and programs in biomedicine Mar 10, 2021
BACKGROUND AND OBJECTIVE: Alzheimer's Disease (AD) is associated with neuronal damage and decrease. Micro-Optical Sectioning Tomography (MOST) provides an approach to acquire high-resolution images for neuron analysis in the whole-brain. Application ...
Neurons Neural Networks, Computer Alzheimer Disease Animals Brain Deep Learning Mice
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Astrocyte regional heterogeneity revealed through machine learning-based glial neuroanatomical assays.

The Journal of comparative neurology Mar 8, 2021
Evaluation of reactive astrogliosis by neuroanatomical assays represents a common experimental outcome for neuroanatomists. The literature demonstrates several conflicting results as to the accuracy of such measures. We posited that the diverging res...
Machine Learning Microscopy, Confocal Astrocytes Gliosis Fluorescent Antibody Technique Animals Image Processing, Computer-Assisted Mice
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Deep learning-based enhancement of epigenomics data with AtacWorks.

Nature communications Mar 8, 2021
ATAC-seq is a widely-applied assay used to measure genome-wide chromatin accessibility; however, its ability to detect active regulatory regions can depend on the depth of sequencing coverage and the signal-to-noise ratio. Here we introduce AtacWorks...
Humans Brain Animals Chromatin Immunoprecipitation Sequencing Leukocytes Deep Learning Mice Regulatory Sequences, Nucleic Acid Epigenomics Chromatin
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Machine learning-based classification of mitochondrial morphology in primary neurons and brain.

Scientific reports Mar 4, 2021
The mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeos...
Humans Machine Learning Nerve Net Image Processing, Computer-Assisted Mitochondrial Dynamics Mice Mitochondria Brain Neurons Animals Microscopy, Electron, Scanning
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