Boosting analyses in the life sciences via clusters, grids and clouds

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Show simple item record Gesing, Sandra Carretero Pérez, Jesús García Blas, Francisco Javier Montagnat, Johan 2021-12-10T11:20:15Z 2021-12-10T11:20:15Z 2017-02-01
dc.identifier.bibliographicCitation Gesing, S., Carretero, J., García Blás, J., Montagnat, J. (2017). Boosting analyses in the life sciences via clusters, grids and clouds. Future Generation Computer Systems, 67, pp. 325-328.
dc.identifier.issn 0167-739X
dc.description.abstract In the last 20 years, computational methods have become an important part of developing emerging technologies for the field of bioinformatics and biomedicine. Those methods rely heavily on large scale computational resources as they need to manage Tbytes or Pbytes of data with large-scale structural and functional relationships, TFlops or PFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analyzing data. This special issue contains papers showing existing solutions and latest developments in Life Sciences and Computing Sciences to collaboratively explore new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making. (C) 2016 Published by Elsevier B.V.
dc.language.iso eng
dc.publisher Elsevier
dc.rights © 2016 Published by Elsevier B.V.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other bioinformatics
dc.subject.other biomedicine
dc.subject.other and health
dc.subject.other genomics
dc.subject.other life sciences
dc.subject.other cloud computing
dc.subject.other workflows
dc.subject.other framework
dc.title Boosting analyses in the life sciences via clusters, grids and clouds
dc.type article
dc.subject.eciencia Informática
dc.rights.accessRights openAccess
dc.type.version submittedVersion
dc.identifier.publicationfirstpage 325
dc.identifier.publicationlastpage 328
dc.identifier.publicationtitle Future Generation Computer Systems-The International Journal of eScience
dc.identifier.publicationvolume 67
dc.identifier.uxxi AR/0000018585
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