YeastMate: neural network-assisted segmentation of mating and budding events in Saccharomyces cerevisiae

Bunk, David; Moriasy, Julian; Thoma, Felix; Jakubke, Christopher; Osman, Christof und Hörl, David (March 2022): YeastMate: neural network-assisted segmentation of mating and budding events in Saccharomyces cerevisiae. In: Bioinformatics, Vol. 38, No. 9: pp. 2667-2669

Abstract

Here, we introduce YeastMate, a user-friendly deep learning-based application for automated detection and segmentation of Saccharomyces cerevisiae cells and their mating and budding events in microscopy images. We build upon Mask R-CNN with a custom segmentation head for the subclassification of mother and daughter cells during lifecycle transitions. YeastMate can be used directly as a Python library or through a standalone application with a graphical user interface (GUI) and a Fiji plugin as easy-to-use frontends.

• Item Type: Journal article
• Faculties: Biology
• Subjects: 500 Science > 570 Life sciences; biology
• ISSN: 1367-4803
• Language: English
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 422857584