Archive for the ‘JPL’ Category

Sage Bionetworks and Amazon SWF

Friday, June 22nd, 2012

Sage Bionetworks and Amazon SWF

From the post:

Over the past couple of decades the medical research community has witnessed a huge increase in the creation of genetic and other bio molecular data on human patients. However, their ability to meaningfully interpret this information and translate it into advances in patient care has been much more modest. The difficulty of accessing, understanding, and reusing data, analysis methods, or disease models across multiple labs with complimentary expertise is a major barrier to the effective interpretation of genomic data. Sage Bionetworks is a non-profit biomedical research organization that seeks to revolutionize the way researchers work together by catalyzing a shift to an open, transparent research environment. Such a shift would benefit future patients by accelerating development of disease treatments, and society as a whole by reducing costs and efficacy of health care.

To drive collaboration among researchers, Sage Bionetworks built an on-line environment, called Synapse. Synapse hosts clinical-genomic datasets and provides researchers with a platform for collaborative analyses. Just like GitHub and Source Forge provide tools and shared code for software engineers, Synapse provides a shared compute space and suite of analysis tools for researchers. Synapse leverages a variety of AWS products to handle basic infrastructure tasks, which has freed the Sage Bionetworks development team to focus on the most scientifically-relevant and unique aspects of their application.

Amazon Simple Workflow Service (Amazon SWF) is a key technology leveraged in Synapse. Synapse relies on Amazon SWF to orchestrate complex, heterogeneous scientific workflows. Michael Kellen, Director of Technology for Sage Bionetworks states, “SWF allowed us to quickly decompose analysis pipelines in an orderly way by separating state transition logic from the actual activities in each step of the pipeline. This allowed software engineers to work on the state transition logic and our scientists to implement the activities, all at the same time. Moreover by using Amazon SWF, Synapse is able to use a heterogeneity of computing resources including our servers hosted in-house, shared infrastructure hosted at our partners’ sites, and public resources, such as Amazon’s Elastic Compute Cloud (Amazon EC2). This gives us immense flexibility is where we run computational jobs which enables Synapse to leverage the right combination of infrastructure for every project.”

The Sage Bionetworks case study (above) and another one, NASA JPL and Amazon SWF, will get you excited about reaching out to the documentation on Amazon Simple Workflow Service (Amazon SWF).

In ways that presentations that consist of reading slides about management advantages to Amazon SWF simply can’t reach. At least not for me.

Take the tip and follow the case studies, then onto the documentation.

Full disclosure: I have always been fascinated by space and really hard bioinformatics problems. And have < 0 interest in DRM antics on material if piped to /dev/null would raise a user's IQ.