AWS HPC Blog
Category: Life Sciences
How Caris Life Sciences processed 400,000 RNAseq samples in 2.5 days with AWS Batch
In the race to deliver precision medicine, time is of the essence. Caris Life Sciences, a pioneer in this field, leveraged AWS Batch to build a highly scalable solution that processed hundreds of thousands of genomic samples in record time. Discover how they achieved this remarkable feat and the key services that powered their breakthrough.
Scalable Cryo-EM on AWS Parallel Computing Service (PCS)
Cryo-EM data processing just got a major boost! Learn how AWS Parallel Computing Service can help structural biology teams scale their HPC infrastructure and streamline Cryo-EM research. Discover a recommended reference architecture that leverages the power of the cloud.
Announcing: Seqera Containers for the bioinformatics community
Genomics community: rejoice! Seqera and AWS have teamed up to announce Seqera Containers, an open-source, no cost, reliable way to generate containers.
Linter rules for Nextflow to improve the detection of errors before runtime
Check out this post to learn how linter rules for Nextflow’s DSL can help you catch errors in your workflows before runtime, which means greater developer productivity, which leads directly to a faster time to science.
Accelerating molecule discovery with computational chemistry and Promethium on AWS
Interested in performing high-accuracy computational chemistry simulations faster? Check out this new post about Promethium, a solution from QC Ware that leverages AWS to accelerate simulations by up to 100x.
Running protein structure prediction at scale using a web interface for researchers
Today, we’ll show you our open-source sample implementation of a web frontend and cloud HPC backend to support researchers using AI tools like AlphaFold for drug discovery and design.
Benchmarking the Oxford Nanopore Technologies basecallers on AWS
Oxford Nanopore sequencers enables direct, real-time analysis of long DNA or RNA fragments. They work by monitoring changes to an electrical current as nucleic acids are passed through a protein nanopore. The resulting signal is decoded to provide the specific DNA or RNA sequence by virtue of compute-intensive algorithms called basecallers. This blog post presents the benchmarking results for two of those Oxford Nanopore basecallers — Guppy and Dorado — on AWS. This benchmarking project was conducted in collaboration between G42 Healthcare, Oxford Nanopore Technologies and AWS.
How Evolvere Biosciences performs macromolecule design on AWS
In this blog post, we catch a glimpse into drug discovery to see how Evolvere Biosciences has deployed a customized architecture w/ AWS Batch and Nextflow to quickly and easily run its macromolecule design pipeline.
BioContainers are now available in Amazon ECR Public Gallery
Today we are excited to announce that all 9000+ applications provided by the BioContainers community are available within ECR Public Gallery! You don’t need an AWS account to access these images, but having one allows many more pulls to the internet, and unmetered usage within AWS. If you perform any sort of bioinformatics analysis on AWS, you should check it out!
Optimize Protein Folding Costs with OpenFold on AWS Batch
In this post, we describe how to orchestrate protein folding jobs on AWS Batch. We also compare the performance of OpenFold and AlphaFold on a set of public targets. Finally, we will discuss how to optimize your protein folding costs.