The rapid advances of Next Generation Sequencing instruments has dropped the cost of acquiring sequencing data dramatically. This has made it possible to sequence a large variety of organisms. However, the side effect of this trend is a big discrepancy between the amount of data that can be collected, and the analysis that can be performed. For example, a single Illumina HiSeq instrument can produce several TBytes in a single run, and many genome centers will have dozens of these instruments running in parallel.
The NGS instrument capability has made it possible to study complete ecosystems of organisms. This new metagenomics involves the analysis of genomic DNA obtained directly from the environment. The goal is to study large scale microbial systems to help diagnose and cure disease. From the functional perspective, a metagenomic sample can be represented as a weighted metabolic network. The functional comparison between metagenomic samples yields insights in the different metabolic subnetworks and thus the workings of the microbial ecosystem.
This metagenomic comparison requires repeated de novo assembly and alignment to characterize the metabolic network. Since these ecosystems can extend to hundreds of thousands of microbes, we are developing better algorithms and hardware acceleration to deliver these classifications.
The Stillwater Knowledge Processing Platform allows bioinformatic researchers to focus on the algorithms. The platform will take care of fast parallel implementations on multi-core, GPU, and FPGA-accelerated hardware.
The size of metagenomic data sets and compute requirements demand large scale cloud-based solutions. The Stillwater Bioinformatics Platform provides a seamless use of cloud computing and cloud storage.
The team at Stillwater is your very own high-tech R&D lab, ready to help solve tomorrow's problems.