CLC bio makes a big move into high-performance computing with turnkey solution for Next Generation Sequencing data analyses
23 Jun 2009At the upcoming 17th international conference on Intelligent Systems for Molecular Biology (ISMB) and 8th European Conference on Computational Biology (ECCB) in Stockholm, Sweden, June 27 – July 2, CLC bio will unveil their first turnkey solution for analyzing and visualizing Next Generation Sequencing data, called CLC Genomics Machine.
The turnkey solution will consist of a hardware platform, a multitude of pre-installed software tools, including various accelerated algorithms for Next Generation Sequencing data analysis, and an enterprise level database - all functioning straight out of the box.
“The release of this system marks a big push into high-performance computing for life sciences and we are confident our solutions will have significant impact in the market – especially when comparing to existing biocomputing solutions, which essentially will be left in the dark with the performance we’re going to deliver,” says Thomas Knudsen, CEO at CLC bio, and continues “To expand our enterprise platform and leverage the best possible turnkey solution, we have partnered with one of the premier technologies available and will shortly announce this partnership.”
CLC bio has conducted initial performance benchmarks which show that the reference assembly of a one-fold coverage human genome can be completed in about one hour. Additionally, the included de novo assembly algorithm will enable de novo assemblies of human genomes as well as large plant genomes on one single CLC Genomics Machine in an astonishingly short time. The CLC Genomics Machine also includes several classic bioinformatics algorithms, like BLASTp, BLASTn, hmmsearch, hmmpfam, Smith-Waterman, and ClustalW. Performance benchmarks of these algorithms against the best-selling off-the-shelf biocomputing FPGA solution, shows an impressive performance advantage with this new turnkey solution from CLC bio.
To read more about CLC Genomics Machine please click the ‘Company article page’ link.