Skip navigation
Please use this identifier to cite or link to this item: http://uvadoc.uva.es/handle/10324/22933
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLarriba González, Yolanda-
dc.contributor.authorRueda Sabater, Cristina-
dc.contributor.authorFernández Temprano, Miguel A.-
dc.date.accessioned2017-03-31T10:52:54Z-
dc.date.available2017-03-31T10:52:54Z-
dc.date.issued2015-
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/22933-
dc.description.abstractIdentification of periodic patterns in gene expression data is important for studying the regulation mechanism of the circadian system. The information available is often given only by one or two cycles. Consequently, the number of observations is not enough to fit certain models, such as Fourier's models, properly. Some authors have already developed procedures or algorithms among which the JTK\_Cycle algorithm is the most popular one. We propose a new method to identify cyclic gene expressions based on circular order restricted inference. Validation of the method is made through real data sets and simulations. Moreover, we compare the results obtained by the method with other detecting methods developed in the literature.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses
dc.titleA new method for identification of cyclic circadian genes using circular isotonic regression.es
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.title.eventXXXV Congreso Nacional de Estadística e Investigación Operativaes
Appears in Collections:DEP24 - Comunicaciones a congresos, conferencias, etc.

Files in This Item:
File Description SizeFormat 
jueves28-extendido.pdf112,1 kBAdobe PDFThumbnail
View/Open

This item is licensed under a Creative Commons License Creative Commons

Suggestions
University of Valladolid
Powered by MIT's. DSpace software, Version 5.5
UVa-STIC