An automated infrastructure to support high-throughput bioinformatics (Articolo in rivista)

Type
Label
  • An automated infrastructure to support high-throughput bioinformatics (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/HPCSim.2014.6903742 (literal)
Alternative label
  • Cuccuru G.; Leo S.; Lianas L.; Muggiri M.; Pinna A.; Pireddu L.; Uva P.; Angius A.; Fotia G.; Zanetti G. (2014)
    An automated infrastructure to support high-throughput bioinformatics
    in High Performance Computing & Simulation (HPCS), 2014 International Conference on
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Cuccuru G.; Leo S.; Lianas L.; Muggiri M.; Pinna A.; Pireddu L.; Uva P.; Angius A.; Fotia G.; Zanetti G. (literal)
Pagina inizio
  • 600 (literal)
Pagina fine
  • 607 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84908632088&partnerID=q2rCbXpz (literal)
Rivista
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IRGB, CNR, CA, Italy CRS4, Pula, CA, Italy (literal)
Titolo
  • An automated infrastructure to support high-throughput bioinformatics (literal)
Abstract
  • The number of domains affected by the big data phenomenon is constantly increasing, both in science and industry, with high-throughput DNA sequencers being among the most massive data producers. Building analysis frameworks that can keep up with such a high production rate, however, is only part of the problem: current challenges include dealing with articulated data repositories where objects are connected by multiple relationships, managing complex processing pipelines where each step depends on a large number of configuration parameters and ensuring reproducibility, error control and usability by non-technical staff. Here we describe an automated infrastructure built to address the above issues in the context of the analysis of the data produced by the CRS4 next-generation sequencing facility. The system integrates open source tools, either written by us or publicly available, into a framework that can handle the whole data transformation process, from raw sequencer output to primary analysis results. (literal)
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