Life sciences research is advancing at a rapid pace and new techniques such as next-generation sequencing (NGS), are playing a vital role in growing scientific knowledge, facilitating the development of targeted drugs, and delivering personalized healthcare.
By investigating the human genome, and studying it in the context of biological pathways and environmental factors, it’s now possible for scientists and clinicians to identify individuals at risk of disease, provide early diagnoses, and recommend effective treatments.
While high-performance computing (HPC) environments were previously deployed mainly in research, genomics is edging ever closer to the patient and front-line clinical care. New sequencing and analysis techniques, a greater emphasis on collaboration, and the application of new technologies like big data and cognitive computing are resulting in a re-think of how computing and storage infrastructure are deployed.
While HPC has an important role to play, application requirements now extend beyond traditional HPC and including many analytic components as well.
In this paper, aimed at IT professionals and bioinformaticians, we review some of the applications of high-performance computing and analytics in healthcare, and describe the software and workloads typically deployed. We then get specific, explaining how an IBM software-defined infrastructure can provide a more capable and efficient platform for the variety of applications and frameworks being deployed in healthcare institutions today.
Client: IBM and Cabot Partners
Date: January 17, 2018
Tags: HPC, Life Sciences