AIMC Topic: Mice
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Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning.
Frontiers in immunology
Apr 16, 2024
BACKGROUND AND AIMS: Cuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusi...
Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation.
Journal of biomedical informatics
Apr 15, 2024
OBJECTIVE: Gene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-...
System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.
Cell research
Apr 11, 2024
The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the ...
Identification of shared potential diagnostic markers in asthma and depression through bioinformatics analysis and machine learning.
International immunopharmacology
Apr 11, 2024
BACKGROUND: There is mounting evidence that asthma might exacerbate depression. We sought to examine candidates for diagnostic genes in patients suffering from asthma and depression.
Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.
PloS one
Mar 29, 2024
Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Mach...
Ultra-sensitive analysis of exhaled biomarkers in ozone-exposed mice via PAI-TOFMS assisted with machine learning algorithms.
Journal of hazardous materials
Mar 27, 2024
Ground-level ozone ranks sixth among common air pollutants. It worsens lung diseases like asthma, emphysema, and chronic bronchitis. Despite recent attention from researchers, the link between exhaled breath and ozone-induced injury remains poorly un...
Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data.
Scientific reports
Mar 27, 2024
The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs). We report that deep learning with a dataset that combines magnetic signa...
GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides.
Scientific reports
Mar 26, 2024
Due to the intricate relationship between the small non-coding ribonucleic acid (miRNA) sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is challenging. Previous methods are not robust and accurate. In this study,...
Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer's Disease Using Biophysical Modeling and Deep Learning.
Bulletin of mathematical biology
Mar 25, 2024
Alzheimer's disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopathy or tauopa...
Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network.
Talanta
Mar 23, 2024
Despite technological advances in the proteomics field, sample preparation still represents the main bottleneck in mass spectrometry (MS) analysis. Bead-based protein aggregation techniques have recently emerged as an efficient, reproducible, and hig...
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