AIMC Topic: Vaccinia virus
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A digital photography dataset for Vaccinia Virus plaque quantification using Deep Learning.
Scientific data
Apr 30, 2025
Virological plaque assay is the major method of detecting and quantifying infectious viruses in research and diagnostic samples. Furthermore, viral plaque phenotypes contain information about the life cycle and spreading mechanism of the virus formin...
Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.
International journal of molecular sciences
Jan 30, 2025
The vaccinia virus (VV) is extensively utilized as a vaccine vector in the treatment of various infectious diseases, cardiovascular diseases, immunodeficiencies, and cancers. The vaccinia virus Tiantan strain (VVTT) has been instrumental as an irrepl...
A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.
Nature communications
Jun 15, 2024
Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here we developed an artificial intelligence (AI)-powered automated framework for ready detection of vir...
Combination of deep XLMS with deep learning reveals an ordered rearrangement and assembly of a major protein component of the vaccinia virion.
mBio
Aug 30, 2023
An outstanding problem in the understanding of poxvirus biology is the molecular structure of the mature virion. Via deep learning methods combined with chemical cross-linking mass spectrometry, we have addressed the structure and assembly pathway of...
Mimicry Embedding Facilitates Advanced Neural Network Training for Image-Based Pathogen Detection.
mSphere
Sep 9, 2020
The use of deep neural networks (DNNs) for analysis of complex biomedical images shows great promise but is hampered by a lack of large verified data sets for rapid network evolution. Here, we present a novel strategy, termed "mimicry embedding," for...
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