Sold by: MIT CSAIL - Regina Barzilay Group
Open data
|
Deployed on AWS
This is the data used to train the Boltz-1 model. It contains the following datasets:
- Our pre-processed version of the Protein Data Bank
- Our pre-processed version of the multiple sequence alignment data for each protein chain
- The raw multiple sequence alginment data.
- A pre-computed symmetry file for symmetry correction during training
Overview
This is the data used to train the Boltz-1 model. It contains the following datasets:
- Our pre-processed version of the Protein Data Bank
- Our pre-processed version of the multiple sequence alignment data for each protein chain
- The raw multiple sequence alginment data.
- A pre-computed symmetry file for symmetry correction during training
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
- S3 Bucket containing the Boltz-1 data
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::boltz1
- AWS region
- us-east-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://boltz1/
Resources
Vendor resources
Support
Contact
Managed By
MIT CSAIL - Regina Barzilay Group
How to cite
Boltz-1 Training Data was accessed on DATE from https://registry.opendata.aws/boltz1 .
License
MIT License
Similar products
This course teaches you how to design, implement, and manage a cloud-based data warehouse using AWS services. Learn best practices for data ingestion, transformation, and analytics with Amazon Redshift and other AWS tools. Ideal for data engineers, analysts, and architects looking to optimize data solutions in the cloud.
Building Agentic AI with Amazon Bedrock AgentCore focuses on designing and deploying autonomous AI agents that can reason, plan, and take actions using foundation models on AWS. The course covers how to orchestrate tools, workflows, and APIs with Bedrock AgentCore to build scalable, secure, and production-ready agentic AI applications.
This course builds on existing cloud architecture knowledge to help design complex, scalable, and resilient solutions on AWS. Learn advanced strategies for networking, security, cost optimisation, and hybrid cloud architectures. Gain hands-on experience with AWS services to enhance performance, automation, and disaster recovery. Ideal for experienced cloud architects looking to deepen their expertise.
This course enables you to dive deep, ask questions, work through solutions, and get feedback from AWS-accredited instructors with deep technical knowledge. This is a fundamental level course and is a part of the AWS Security learning path.