English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/168080
COMPARTIR / IMPACTO:
Estadísticas
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Campo DC Valor Lengua/Idioma
dc.contributor.authorTauler, Romàes_ES
dc.contributor.authorParastar, H.es_ES
dc.date.accessioned2018-07-31T13:43:41Z-
dc.date.available2018-07-31T13:43:41Z-
dc.date.issued2018-03-23-
dc.identifier.citationAngewandte Chemie - International Edition (2018)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/168080-
dc.description.abstractThis review aims to demonstrate abilities to analyze Big (Bio)Chemical Data (BBCD) with multivariate chemometric methods and to show some of the more important challenges of modern analytical researches. In this review, the capabilities and versatility of chemometric methods will be discussed in light of the BBCD challenges that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements, with an emphasis on their application to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this review, the importance of Big Data and of their relevance to (bio)chemistry are first discussed. Then, analytical tools which can produce BBCD are presented as well as some basics needed to understand prospects and limitations of chemometric techniques when they are applied to BBCD are given. Finally, the significance of the combination of chemometric approaches with BBCD analysis in different chemical disciplines is highlighted with some examples. In this paper, we have tried to cover some of the applications of big data analysis in the (bio)chemistry field. However, this coverage is not extensive covering everything done in the field.es_ES
dc.description.sponsorshipHadi Parastar would like to thank Sharif University of Technology (SUT) of Iran for financial support for a short sabbatical leave at IDAEA-CSIC of Barcelona. Roma Tauler would like to thank the European Research Council for the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 320737.es_ES
dc.language.isoenges_ES
dc.publisherWiley-VCHes_ES
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/320737es_ES
dc.relation.isversionofPostprintes_ES
dc.rightsclosedAccesses_ES
dc.subjectChemometricses_ES
dc.subjectBig Dataes_ES
dc.subjectOmics Sciencees_ES
dc.subjectChromatographyes_ES
dc.subjectmass spectrometryes_ES
dc.titleBig (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemistses_ES
dc.typeArtículoes_ES
dc.identifier.doi10.1002/anie.201801134-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversion10.1002/anie.201801134es_ES
dc.embargo.terms2019-03-23es_ES
dc.contributor.funderEuropean Commissiones_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
Aparece en las colecciones: (IDAEA) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
Big (Bio)Chemical Data Mining Using Chemometric Methods A Need for Chemists.docx Embargado hasta 23 de marzo de 201912,43 MBMicrosoft Word XMLVisualizar/Abrir     Petición de una copia
Show simple item record
 

Artículos relacionados:


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.