Sugimura lab at the Department of Bioinformatics and Systems Biology, Faculty of Science, The University of Tokyo 東京大学理学部杉村研究室 機械的な力による多細胞秩序形成原理を研究しています
Really enjoyed my first EMBO Fly Meeting. Many thanks to the organizers for the opportunity. The work on cell-size control that I presented at the meeting has just been published, together with a “People Behind the Paper” interview.
https://t.co/dXR25BzdIG
https://t.co/w7dbuXaTzG
Most beautiful graph I’ve ever plotted: precise control of average cell size emerging from the frequencies and size dynamics of distinct division lineages in Drosophila wing.
More on spatiotemporal division dynamics, see: https://t.co/1V9n58nRRh
To actin and adhesion lovers in the Fly community, we’re pleased to announce that a GFP knock-in line for Coronin-1, a WD-repeat actin-binding protein, is now available from the Kyoto Stock Center.
Stock: https://t.co/nbO1dE8qff
Original publication: https://t.co/ZkejDQpFYO
New preprint! Using in vivo data of epithelial development, we demonstrate the compatibility of strain rate tensors and the accuracy of kinematic equations. The results cross-validate the modified texture analysis and our hydrodynamic model.
https://t.co/3Oc0kPKJ8c
Xin received the Excellent Research Award based on her master’s thesis. Congratulations!
M2の厳欣さんが東京大学大学院新領域創成科学研究科メディカル情報生命専攻のExcellent Research Award優秀賞を受賞しました。
https://t.co/ZLgzd1u82H
Bayesian Force Inference is now on Google colab!
Together with GetVertex, an ImageJ/Fiji plugin for extracting input data from skeletonized images, this enables code-free quantification of forces during epithelial development.
https://t.co/pkzz266yrI
Happy to share GetVertex, an ImageJ/Fiji plugin that extracts vertex positions and connectivity from skeletonized images.
The output text file can be used as input for Bayesian Force Inference and Image-based Parameter Inference for Epithelial Mechanics.
https://t.co/ruEgG9wFrh
Bayesian parameter inference for epithelial mechanics has been published in a topical issue of the Journal of Theoretical Biology, edited by @JochenKursawe and Nikolaos Sfakianakis. This is the first paper by our master’s student, Xin Yan. Congrats, Xin!
https://t.co/O6hzTPGUDB
New preprint! We employed Bayesian statistics to improve the utility and flexibility of image-based parameter inference, a statistical framework to construct functions of Cell Vertex Model and estimate their parameters from image data.
https://t.co/hgV4D0WNhZ
@tetsuotani1 Last but not least, we thank the reviewers for their constructive comments and suggestions, which helped us significantly improve this review.
Happy to see our review on vertex remodeling out! Exciting collaboration with @tetsuotani1. Highlights include EM image of end-on actin filaments attached around the cell vertex and new modeling frameworks to analyze mechanics at the cell vertex.
https://t.co/bnq7zTCJmZ
I finally had the chance to work with my respected senpai (先輩) @tetsuotani1. We met at Takeichi Lab when I was an undergraduate, and I learned a lot from him during the writing process.
Mechanical forces can affect the way tissue grows. Ideally, we want to characterize them without interfering with the processes we are studying. Is there a way to achieve this?
I am @borgesaugust. Welcome to my stress inference tutorial!
#EpithelialMechanics