Category: AWS Batch
Computational biology is undergoing a revolution. However, the analysis of single cells is a hard problem to solve. Standard statistical techniques used in genomic analysis fail to capture the complexity present in single-cell datasets. Open Problems in Single-Cell Analysis is a community-driven effort using AWS to drive the development of novel methods that leverage the power of single-cell data.
Scientists at NC State University’s North Carolina Institute for Climate Studies (NCICS) work with large datasets and complex computational analysis. Traditionally, they did their work using on-premises computational resources. As different projects were stretching the limits of those systems, NCICS decided to explore cloud computing. As part of the Amazon Sustainability Data Initiative, we invited Jessica Mathews, Jared Rennie, and Tom Maycock to share what they learned from using AWS for climate research. As they considered exploring the cloud to support their work, the idea of leaving the comfort of the local environment was a bit scary. And they had questions: How much will it cost? What does it take to deploy processing to the cloud? Will it be faster? Will the results match what they were getting with their own systems? Here is their story and what they learned.