CryoET Data Portal | Documentation¶
The Chan Zuckerberg Institute for Advanced Biological Imaging (CZ Imaging Institute) has made a beta release of the CryoET Data Portal providing queryable and organized data from CryoET experiments. Each of the over 15,000 tomograms on the Portal have at least one structure annotated.
This site provides additional documentation for using our Python API to query and download data and for navigating the CryoET Data Portal and its visualization tools. We hope this site will assist segmentation algorithm developers to produce annotations for diverse macromolecules in the tomograms that may be used for high-resolution subtomogram averaging.
We welcome feedback from the community on the data structure, design and functionality.
Share first impressions, or sign up for invites to future feedback activities in this short form.
Submit bugs for the CryoET Data Portal via GitHub issues.
Start a Github discussion with questions or to request new features.
Getting Started¶
Install and start using the Python Client API
Information on the Python Client API Classes
Examples of selecting, downloading, and visualizing data from the Portal
Learn about CryoET data and how to navigate the CryoET Data Portal
Amazon Web Services S3 Bucket Info¶
The CryoET Data Portal S3 bucket supports public access. The bucket URL is:
s3://cryoet-data-portal-public
To list the bucket contents with the S3 CLI without credentials, please use the following:
aws s3 ls --no-sign-request s3://cryoet-data-portal-public
Refer to this how-to guide for information on downloading data from our AWS S3 bucket.
Citing the CryoET Data Portal¶
Data from the portal must acknowledge the data providers and the original publications. The following is provided as an example:
Some of the data used in this work was provided by the group(s) of Julia Mahamid (EMBL)/Jürgen Plitzko (MPI) [see beta site for current details]. The work is described more fully in the publication:
Provider |
Julia Mahamid |
Julia Mahamid |
Jürgen Plitzko |
---|---|---|---|
Dataset name |
10000 |
10001 |
10004 |
Acknowledgement |
Note
Segmentation experts and developers are also encouraged to get in touch with the data providers if they feel they have developed a useful tool that might help to process the entirety of the datasets (which are much larger than the subsets provided for the portal) more efficiently or effectively.