AIMC Topic: Mice, Transgenic

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A Novel Morphological Marker for the Analysis of Molecular Activities at the Single-cell Level.

Cell structure and function
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...

Fully automated, deep learning segmentation of oxygen-induced retinopathy images.

JCI insight
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...

Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency.

Journal of neural engineering
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....

Forestwalk: A Machine Learning Workflow Brings New Insights Into Posture and Balance in Rodent Beam Walking.

The European journal of neuroscience
The beam walk is widely used to study coordination and balance in rodents. While the task has ethological validity, the main endpoints of "foot slip counts" and "time to cross" are prone to human-rater variability and offer limited sensitivity and sp...

Machine Learning-Supported Analyses Improve Quantitative Histological Assessments of Amyloid-β Deposits and Activated Microglia.

Journal of Alzheimer's disease : JAD
BACKGROUND: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automa...

Complementary feature selection from alternative splicing events and gene expression for phenotype prediction.

Bioinformatics (Oxford, England)
MOTIVATION: A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via g...

Use of a Machine Learning-Based High Content Analysis Approach to Identify Photoreceptor Neurite Promoting Molecules.

Advances in experimental medicine and biology
High content analysis (HCA) has become a leading methodology in phenotypic drug discovery efforts. Typical HCA workflows include imaging cells using an automated microscope and analyzing the data using algorithms designed to quantify one or more spec...

Mapping Sub-Second Structure in Mouse Behavior.

Neuron
Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that 3D mouse pose dynamics are structured at the sub-second timescale. ...