| Literature DB >> 20865556 |
Christopher E Mason1, Paul Zumbo, Stephan Sanders, Mike Folk, Dana Robinson, Ruth Aydt, Martin Gollery, Mark Welsh, N Eric Olson, Todd M Smith.
Abstract
Next Generation Sequencing technologies are limited by the lack of standard bioinformatics infrastructures that can reduce data storage, increase data processing performance, and integrate diverse information. HDF technologies address these requirements and have a long history of use in data-intensive science communities. They include general data file formats, libraries, and tools for working with the data. Compared to emerging standards, such as the SAM/BAM formats, HDF5-based systems demonstrate significantly better scalability, can support multiple indexes, store multiple data types, and are self-describing. For these reasons, HDF5 and its BioHDF extension are well suited for implementing data models to support the next generation of bioinformatics applications.Mesh:
Year: 2010 PMID: 20865556 DOI: 10.1007/978-1-4419-5913-3_77
Source DB: PubMed Journal: Adv Exp Med Biol ISSN: 0065-2598 Impact factor: 2.622