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

Gesing, Sandra; Carretero Pérez, Jesús; García Blas, Francisco Javier; Montagnat, Johan

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

dc.affiliation.dpto	UC3M. Departamento de Informática	es
dc.affiliation.grupoinv	UC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemas	es
dc.contributor.author	Gesing, Sandra
dc.contributor.author	Carretero Pérez, Jesús
dc.contributor.author	García Blas, Francisco Javier
dc.contributor.author	Montagnat, Johan
dc.date.accessioned	2021-12-10T11:20:15Z
dc.date.available	2021-12-10T11:20:15Z
dc.date.issued	2017-02-01
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.	en
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. https://doi.org/10.1016/j.future.2016.11.001	en
dc.identifier.doi	https://doi.org/10.1016/j.future.2016.11.001
dc.identifier.issn	0167-739X
dc.identifier.publicationfirstpage	325
dc.identifier.publicationlastpage	328
dc.identifier.publicationtitle	Future Generation Computer Systems-The International Journal of eScience	en
dc.identifier.publicationvolume	67
dc.identifier.uri	https://hdl.handle.net/10016/33739
dc.identifier.uxxi	AR/0000018585
dc.language.iso	eng	en
dc.publisher	Elsevier	en
dc.rights	© 2016 Published by Elsevier B.V.	en
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRights	open access	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.eciencia	Informática	es
dc.subject.other	bioinformatics	en
dc.subject.other	biomedicine	en
dc.subject.other	and health	en
dc.subject.other	genomics	en
dc.subject.other	life sciences	en
dc.subject.other	cloud computing	en
dc.subject.other	workflows	en
dc.subject.other	framework	en
dc.title	Boosting analyses in the life sciences via clusters, grids and clouds	en
dc.type	research article	*
dc.type.hasVersion	SMUR	*
dspace.entity.type	Publication