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Geospiza and The HDF Group awarded Phase II STTR Grant to Develop Portable, Scalable SAN DIEGO, CA – March 17, 2009 – Geospiza, Inc., the market leading developer of genetic analysis software, and The HDF
Group today announced their collaboration to develop scalable bioinformatics technologies to support multiple Next Generation This collaboration builds on Geospiza’s commitment to work with the scientific and open source community to solve challenging issues related to scalable and cost effective genetic analysis. Geospiza’s software, GeneSifter® integrates many open source technologies like mapreads and MAQ as well as the R-statistical package to provide best-of-breed, peer-reviewed solutions to customers. "We are looking forward to continuing our work with The HDF Group to find new ways to address the data analysis and data
management challenges created by Next Gen Sequencing,” said Todd Smith, founder and Chief Scientific Officer of Geospiza.
“Widespread adoption of Next Gen sequencing is hindered because current bioinformatics approaches to working with these data
simply do not scale. While Geospiza’s hosted computing model solves many of the basic workflow issues faced by current desktop
applications, more complex challenges arise when multiple analyses need to be performed. It is clear that 2nd and 3rd generation "The HDF Group is thrilled that the NIH has funded us to work with Geospiza on the data challenges posed by Next Gen Sequencing. Hundreds of applications, from flight testing to global climate research, already use the HDF data formats and software infrastructure to manage and access high volume, complex data,” stated Mike Folk, president of The HDF Group. “Geospiza has been visionary on seeing how data intensive genomics applications can benefit from technologies like HDF that are designed to work with the specific features and attributes of scientific data." Folk continued, “BioHDF will be a new face on top of the HDF infrastructure, making it seamless and easy to use by the
bioinformatics community. Under the hood, we will extend and tune HDF to address unique challenges of genomic data, such as
organizing and accessing tens of millions of sequences in complex workflows, and capturing the complex interrelationships among
the myriad layers of data and information involved in even the simplest studies." About Geospiza For more information, please contact: |
Super Computing 09 and BioHDF |
