• español
  • English
  • français
  • Deutsch
  • português (Brasil)
  • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Stöbern

    Gesamter BestandBereicheErscheinungsdatumAutorenSchlagwortenTiteln

    Mein Benutzerkonto

    Einloggen

    Statistik

    Benutzungsstatistik

    Compartir

    Dokumentanzeige 
    •   UVaDOC Startseite
    • WISSENSCHAFTLICHE ARBEITEN
    • Departamentos
    • Dpto. Estadística e Investigación Operativa
    • DEP24 - Comunicaciones a congresos, conferencias, etc.
    • Dokumentanzeige
    •   UVaDOC Startseite
    • WISSENSCHAFTLICHE ARBEITEN
    • Departamentos
    • Dpto. Estadística e Investigación Operativa
    • DEP24 - Comunicaciones a congresos, conferencias, etc.
    • Dokumentanzeige
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano

    Exportar

    RISMendeleyRefworksZotero
    • edm
    • marc
    • xoai
    • qdc
    • ore
    • ese
    • dim
    • uketd_dc
    • oai_dc
    • etdms
    • rdf
    • mods
    • mets
    • didl
    • premis

    Citas

    Por favor, use este identificador para citar o enlazar este ítem:http://uvadoc.uva.es/handle/10324/22933

    Título
    A new method for identification of cyclic circadian genes using circular isotonic regression.
    Autor
    Larriba González, YolandaAutoridad UVA Orcid
    Rueda Sabater, María CristinaAutoridad UVA
    Fernández Temprano, Miguel AlejandroAutoridad UVA Orcid
    Congreso
    XXXV Congreso Nacional de Estadística e Investigación Operativa
    Año del Documento
    2015
    Zusammenfassung
    Identification 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.
    Idioma
    eng
    URI
    http://uvadoc.uva.es/handle/10324/22933
    Derechos
    restrictedAccess
    Aparece en las colecciones
    • DEP24 - Comunicaciones a congresos, conferencias, etc. [18]
    Zur Langanzeige
    Dateien zu dieser Ressource
    Nombre:
    jueves28-extendido.pdf
    Tamaño:
    112.0Kb
    Formato:
    Adobe PDF
    Thumbnail
    Öffnen
    Nombre:
    abstract.v3.pdf
    Tamaño:
    5.193Kb
    Formato:
    Adobe PDF
    Thumbnail
    Öffnen
    Attribution-NonCommercial-NoDerivatives 4.0 InternationalSolange nicht anders angezeigt, wird die Lizenz wie folgt beschrieben: Attribution-NonCommercial-NoDerivatives 4.0 International

    Universidad de Valladolid

    Powered by MIT's. DSpace software, Version 5.10