CryoET Data Annotation Machine Learning Competition
Develop a ML model for annotating subcellular structures and proteins in CryoET data
Starts
Fall 2024
Prizes
$50k Total
About the Competition
Cryogenic Electron Tomography (CryoET) is an advanced imaging technique for visualizing cellular structures at near-atomic resolution. CryoET has led to significant scientific advances in our understanding of protein structure, cellular function, and disease. These insights come from analyzing annotated CryoET data where different parts of the cell and even individual proteins are segmented.
However, annotating CryoET data by hand is very time-consuming, taking weeks or months for a single dataset. In addition, particle picking, the annotation process of identifying particles of interest within tomograms, is challenging, especially for particles smaller than ribosomes since CryoET data has a low signal-to-noise ratio compared to other imaging modalities. Particle picking is generally done by template matching, which compares a predefined template to potential regions containing the particles of interest in the tomograms. Once particles are picked, they are aligned and averaged to reconstruct structures at near-atomic resolutions, providing insights into cellular mechanisms.
Our machine learning competition focuses on enhancing particle picking for a range of particle sizes through the development of machine learning models to generate semantic segmentation masks within 3D CryoET tomograms. The primary aim is to refine the template matching process by identifying areas of interest where template matching should be concentrated. This method narrows down the search space, thereby boosting the accuracy and efficiency of the CryoET computational workflow. Participants are tasked with crafting models that produce masks highlighting the precise locations for template matching, facilitating the identification of specific particles across various tomograms.
Competition Details
More info coming soon
How to Participate
More info coming soon
Competition Data
Competition Dataset:
Coming in Fall 2024
The competition dataset will be published on the Portal when the Competition starts Fall 2024.
In the meantime, you can explore other CryoET datasets in the Data Portal.
About CryoET Data
More info coming soon
Tutorials
Example notebooks for existing models, such as TomoTwin and DeepFinder, are provided to serve as onboarding materials and baseline solutions. These examples include preliminary results to set performance benchmarks for the competition.
Coming in Fall 2024
About the Organizers
Bridget Carragher
Chan Zuckerberg Imaging Institute (CZII)
Anchi Cheng
Chan Zuckerberg Imaging Institute (CZII)
Utz Ermel
Chan Zuckerberg Imaging Institute (CZII)
Kyle Harrington
Chan Zuckerberg Imaging Institute (CZII)
Reza Paraan
Chan Zuckerberg Imaging Institute (CZII)
Jonathan Schwartz
Chan Zuckerberg Imaging Institute (CZII)
Daniel Serwas
Chan Zuckerberg Imaging Institute (CZII)
Hannah Siems
Chan Zuckerberg Imaging Institute (CZII)
Yue Yu
Chan Zuckerberg Imaging Institute (CZII)
Kevin Zhao
Chan Zuckerberg Imaging Institute (CZII)
Sponsored By:
FAQ
More info coming soon
Contact
Have more questions? Reach out to Dannielle McCarthy at dmccarthy@chanzuckerberg.com