Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/11810
COMPARTIR / EXPORTAR:
logo share SHARE logo core CORE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invitar a revisión por pares abierta
Título

Exploratory data analysis of DNA microarrays by multivariate curve resolution

AutorJaumot, Joaquim CSIC ORCID ; Tauler, Romà CSIC ORCID; Gargallo, Raimundo
Palabras claveGene expression data
DNA microarray
Multivariate curve resolution
Cancer
Fecha de publicación1-nov-2006
EditorElsevier
CitaciónAnalytical and Bioanalytical Chemistry 3358(1):76-89(2006)
ResumenIn this work, the application of a multivariate curve resolution procedure based on alternating least squares optimization (MCR-ALS) for the analysis of data from DNA microarrays is proposed. For this purpose, simulated and publicly available experimental data sets have been analyzed. Application of MCR-ALS, a method that operates without the use of any training set, has enabled the resolution of the relevant information about different cancer lines classification using a set of few components; each of these defined by a sample and a pure gene expression profile. From resolved sample profiles, a classification of samples according to their origin is proposed. From the resolved pure gene expression profiles, a set of over- or underexpressed genes that could be related to the development of cancer diseases has been selected. Advantages of the MCR-ALS procedure in relation to other previously proposed procedures such as principal component analysis are discussed.
Descripción14 pages, 3 tables, 4 figures.
Versión del editorhttp://dx.doi.org/10.1016/j.ab.2006.07.028
URIhttp://hdl.handle.net/10261/11810
DOI10.1016/j.ab.2006.07.028
ISSN1618-2642
E-ISSN1618-2650
Aparece en las colecciones: (IDAEA) Artículos

Mostrar el registro completo

CORE Recommender

SCOPUSTM   
Citations

31
checked on 18-abr-2024

WEB OF SCIENCETM
Citations

27
checked on 25-feb-2024

Page view(s)

336
checked on 18-abr-2024

Google ScholarTM

Check

Altmetric

Altmetric


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