OPERA-gSAM: Big Data Processing Framework for UMI Sequencing at High Scalability and Efficiency

  1. Caderno, P.V.
  2. Awaysheh, F.M.
  3. Colino-Sanguino, Y.
  4. Fuente, L.R.D.L.
  5. Valdes-Mora, F.
  6. Cabaleiro, J.C.
  7. Pena, T.F.
  8. Gallego-Ortega, D.
Konferenzberichte:
Proceedings - 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing Workshops, CCGridW 2023

ISBN: 9798350302080

Datum der Publikation: 2023

Seiten: 160-167

Art: Konferenz-Beitrag

DOI: 10.1109/CCGRIDW59191.2023.00038 GOOGLE SCHOLAR

Objetivos de desarrollo sostenible

Datenquelle: Scopus