DNA sequencing of a single human genome can potentially produce several hundred gigabytes of data, which includes billions of DNA fragments. With rapidly increasing data, how to arrive at optimized, faster, and less expensive experimenting and DNA sequencing? In this space, we bring to you stories from leading organizations in healthcare and genomics research, about how they scaled up their research with Google’s powerful storage and computational Cloud platform…
Data storage and compute power in the life sciences and bio-tech industry are critical to sustain growth and to enable quicker medical discoveries. Big genomic data is here today, with petabytes rapidly growing toward exabytes. Processing millions of genomes and handling massive all-by-all comparisons of genomic information across them, takes more compute power than even the best university or private clusters offer.
At LabAgility, we are often contacted by scientists, researchers, pathological groups, universities, and labs with one same question – How to accelerate quality research at overall reduced spend?
With this post, our goal is to practically ‘show’ through examples and stories than pouring down opinions and observations. Hence we have compiled some customer stories where we helped major organizations from life sciences and genomics data research communities, leverage the power of Google Genomics and Google Cloud platform to securely store, process, explore, organize, interpret, and share large, complex biological datasets, improve research, and run more experiments everyday.