Open data
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Deployed on AWS
This dataset includes data and models relevant to benchmarking multimodal biological models. The data has been sourced and curated by a team of experts at CZI and is provided as part of these datasets only when it is not publicly available or requires transformation to support effective model benchmarking.
Overview
This dataset includes data and models relevant to benchmarking multimodal biological models. The data has been sourced and curated by a team of experts at CZI and is provided as part of these datasets only when it is not publicly available or requires transformation to support effective model benchmarking.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- CZI Benchmarking data
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::cz-benchmarks-data
- AWS region
- us-west-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://cz-benchmarks-data/
Resources
Vendor resources
Support
Contact
Managed By
How to cite
CZ Grand Challenges - Model Benchmarking was accessed on DATE from https://registry.opendata.aws/czi-benchmarking .
License
CC0 1.0
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"This dataset contains the training data for the Tumor InfiltratinG lymphocytes in breast cancER or TIGER challenge. TIGER is the first challenge on fully automated assessment of tumor-infiltrating lymphocytes (TILs) in breast cancer histopathology slides. TILs are proving to be an important biomarker in cancer patients as they can play a part in killing tumor cells, particularly in some types of breast cancer. Identifying and measuring TILs can help to better target treatments, particularly immunotherapy, and may result in lower levels of other more aggressive treatments, including chemotherapy."