AIMC Topic: Vacuoles

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Automated quantification of vacuole fusion and lipophagy in from fluorescence and cryo-soft X-ray microscopy data using deep learning.

Autophagy Oct 31, 2023
During starvation in the yeast vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and...
Deep Learning Autophagy Microscopy, Fluorescence Saccharomyces cerevisiae Saccharomyces cerevisiae Proteins Lipid Droplets Vacuoles Tomography, X-Ray
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Utilization of a Deep Learning Algorithm for Microscope-Based Fatty Vacuole Quantification in a Fatty Liver Model in Mice.

Toxicologic pathology Jun 8, 2020
Quantification of fatty vacuoles in the liver, with differentiation from lumina of liver blood vessels and bile ducts, is an example where the traditional semiquantitative pathology assessment can be enhanced with artificial intelligence (AI) algorit...
Artificial Intelligence Machine Learning Algorithms Animals Deep Learning Mice Disease Models, Animal Liver Non-alcoholic Fatty Liver Disease Microscopy Image Interpretation, Computer-Assisted Vacuoles
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VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques.

Journal of biosciences Jan 1, 2020
Subcellular localization prediction of the proteome is one of major goals of large-scale genome or proteome sequencing projects to define the gene functions that could be possible with the help of computational modeling techniques. Previously, differ...
Software ROC Curve Computational Biology Proteome Support Vector Machine Databases, Protein Datasets as Topic Plant Proteins Plant Cells Viridiplantae Vacuoles
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