A5100513675- Single-cell and spatial transcriptomics
- Cancer Genomics and Diagnostics
- Congenital heart defects research
- Cell Image Analysis Techniques
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Long-Term Effects of COVID-19
- Advanced Computational Techniques and Applications
- Muscle Physiology and Disorders
- RNA modifications and cancer
- Chromosomal and Genetic Variations
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Smart Grid and Power Systems
- Power Systems and Technologies
McGill University Health Centre
2024-2025
McGill University
2023-2025
Wuhan University
2010
ABSTRACT Background COVID‐19 has been associated with both respiratory (diaphragm) and non‐respiratory (limb) muscle atrophy. It is unclear if SARS‐CoV‐2 infection of skeletal plays a role in these changes. This study sought to: 1) determine cells comprising tissue, particularly myofibres, express the molecular components required for infection; 2) assess capacity direct its impact on atrophy pathway genes myogenic cells; 3) an animal model COVID‐19, examine relationship between viral...
<title>Abstract</title> Single-cell RNA sequencing (scRNA-seq) offers unparalleled resolution for studying cellular heterogeneity but is costly, restricting its use to small cohorts that often lack comprehensive clinical data, limiting translational relevance. In contrast, bulk scalable and cost-effective obscures critical single-cell insights. We introduce SIDISH, a neural network framework integrates the granularity of scRNA-seq with scalability RNA-seq. Using Variational Autoencoder, deep...
Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either 'best-mapped' or 'random-mapped' locations categorize them at the subfamily levels, overlooking biological necessity accurate, locus-specific TE quantification. Moreover, these existing primarily designed focused on transcriptomics data, which restricts their adaptability data of other modalities. To address challenges, here...
Abstract Human diseases are characterized by intricate cellular dynamics. Single-cell sequencing provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in-silico drug interventions. We introduce UNAGI, deep generative neural network tailored to analyze time-series single-cell transcriptomic data. This innovative tool captures the complex dynamics underlying progression, enhancing perturbation modeling discovery....
Based on the surveying of condition based maintenance technology organized by China Three Gorges Project Company, condition-based system for hydroelectric generating unit and its application environment are discussed in this paper. Its function, structure characters research hotspots summarized also, combining with some instances applied practice. The advice is given at same time.