AIMC Topic: Mice

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Facemap: a framework for modeling neural activity based on orofacial tracking.

Nature neuroscience
Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relat...

A systematic review of the development and application of home cage monitoring in laboratory mice and rats.

BMC biology
BACKGROUND: Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors an...

Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra.

Communications biology
Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilised DLAP to analyse su...

Accurate classification of major brain cell types using in vivo imaging and neural network processing.

PLoS biology
Comprehensive analysis of tissue cell type composition using microscopic techniques has primarily been confined to ex vivo approaches. Here, we introduce NuCLear (Nucleus-instructed tissue composition using deep learning), an approach combining in vi...

High-Content Image-Based Screening and Deep Learning for the Detection of Anti-Inflammatory Drug Leads.

Chembiochem : a European journal of chemical biology
We developed a high-content image-based screen that utilizes the pro-inflammatory stimulus lipopolysaccharide (LPS) and murine macrophages (RAW264.7) with the goal of enabling the identification of novel anti-inflammatory lead compounds. We screened ...

Combined colour deconvolution and artificial intelligence approach for region-selective immunohistochemical labelling quantification: The example of alpha smooth muscle actin in mouse kidney.

Journal of biophotonics
Immunohistochemical (IHC) localisation of protein expression is a widely used tool in pathology. This is semi-quantitative and exhibits substantial intra- and inter-observer variability. Digital approaches based on stain quantification applied to IHC...

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Journal of chemical information and modeling
Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of...

Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence.

mBio
Vaccines to curb the global spread of multidrug-resistant gonorrhea are urgently needed. Here, 26 vaccine candidates identified by an artificial intelligence-driven platform (Efficacy Discriminative Educated Network[EDEN]) were screened for efficacy ...

DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype-phenotype prediction.

Genome medicine
BACKGROUND: Genotypes are strongly associated with disease phenotypes, particularly in brain disorders. However, the molecular and cellular mechanisms behind this association remain elusive. With emerging multimodal data for these mechanisms, machine...

PINK1 dominated mitochondria associated genes signature predicts abdominal aortic aneurysm with metabolic syndrome.

Biochimica et biophysica acta. Molecular basis of disease
Abdominal aortic aneurysm (AAA) is typically asymptomatic but a devastating cardiovascular disorder, with overall mortality exceeding 80 % once it ruptures. Some patients with AAA may also have comorbid metabolic syndrome (MS), suggesting a potential...