Expanding TheCellVision.org: a central repository for visualizing and mining high-content cell imaging projects.
Myra Paz David Masinas1, Athanasios Litsios1, Anastasia Razdaibiedina1,2,3
1The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
Genetics
|March 22, 2024
Summary
TheCellVision.org expands its yeast high-content imaging data repository with new cell cycle and functional annotation projects. This resource now offers over 800,000 images and enhanced tools for eukaryotic single-cell biology research.
Area of Science:
- Cell Biology
- Bioinformatics
- Genomics
Background:
- TheCellVision.org was established as a repository for yeast high-content screening (HCS) data.
- Initial data included genome-scale protein abundance, localization, and endocytic morphology analyses for Saccharomyces cerevisiae.
- The resource aimed to facilitate visualization and mining of HCS data.
Purpose of the Study:
- To report the expansion of TheCellVision.org with new HCS projects and global functionalities.
- To integrate the Cell Cycle Omics project and the PIFiA computational tool.
- To enhance the resource's utility for single-cell eukaryotic biology research.
Main Methods:
- Addition of the Cell Cycle Omics project, detailing cell cycle-resolved dynamics of protein localization, concentration, gene expression, and translational efficiency.
- Incorporation of PIFiA, a tool for image-based prediction of protein functional annotations.
- Expansion of global functionalities, including cross-species gene querying (yeast/human).
Main Results:
- TheCellVision.org now hosts images from the Cell Cycle Omics project.
- The PIFiA computational tool is integrated for functional annotation predictions.
- The repository contains over 800,000 microscopy images and associated datasets.
- New functionalities allow querying genes using both yeast and human gene names.
Conclusions:
- TheCellVision.org has significantly expanded its data and tools.
- The updated resource provides a more comprehensive platform for yeast HCS data analysis.
- It serves as an increasingly valuable resource for single-cell eukaryotic biology research.
