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A First-Stage Approximation to Identify New Imprinted Genes through Sequence Analysis of Its Coding Regions

  • Dades identificatives

    Identificador: imarina:5824931
    Autors:
    Daura-Oller, EliasCabre, MariaMontero, Miguel A.Paternain, Jose L.Romeu, Antoni
    Resum:
    In the present study, a positive training set of 30 known human imprinted gene coding regions are compared with a set of 72 randomly sampled human nonimprinted gene coding regions (negative training set) to identify genomic features common to human imprinted genes. The most important feature of the present work is its ability to use multivariate analysis to look at variation, at coding region DNA level, among imprinted and non-imprinted genes. There is a force affecting genomic parameters that appears through the use of the appropriate multivariate methods (principle components analysis (PCA) and quadratic discriminant analysis (QDA) to analyse quantitative genomic data. We show that variables, such as CG content, [bp]% CpG islands, [bp]% Large Tandem Repeats, and [bp]% Simple Repeats, are able to distinguish coding regions of human imprinted genes.
  • Altres:

    Autor segons l'article: Daura-Oller, Elias; Cabre, Maria; Montero, Miguel A.; Paternain, Jose L.; Romeu, Antoni;
    Departament: Química Física i Inorgànica
    Autor/s de la URV: Cabré Bargalló, Maria / DAURA OLLER, ELIES / Montero Simó, Miguel Angel / PATERNÁIN SUBERVIOLA, JOSÉ LUIS / ROMEU FIGUEROLA, ANTONIO RAMÓN
    Paraules clau: @infoAeu @residentesaeu @uroweb Etiqueta «#» Hashtag
    Resum: In the present study, a positive training set of 30 known human imprinted gene coding regions are compared with a set of 72 randomly sampled human nonimprinted gene coding regions (negative training set) to identify genomic features common to human imprinted genes. The most important feature of the present work is its ability to use multivariate analysis to look at variation, at coding region DNA level, among imprinted and non-imprinted genes. There is a force affecting genomic parameters that appears through the use of the appropriate multivariate methods (principle components analysis (PCA) and quadratic discriminant analysis (QDA) to analyse quantitative genomic data. We show that variables, such as CG content, [bp]% CpG islands, [bp]% Large Tandem Repeats, and [bp]% Simple Repeats, are able to distinguish coding regions of human imprinted genes.
    Àrees temàtiques: Molecular biology Medicina i Genetics & heredity Genetics Biotechnology & applied microbiology Biotechnology Biodiversidade Biochemistry & molecular biology
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 1531-6912
    Adreça de correu electrònic de l'autor: maria.cabre@urv.cat
    Identificador de l'autor: 0000-0003-4124-8603
    Data d'alta del registre: 2024-09-28
    Volum de revista: 2009
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.hindawi.com/journals/ijg/2009/549387/
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Comparative And Functional Genomics. 2009 (549387): 549387-
    Referència de l'ítem segons les normes APA: Daura-Oller, Elias; Cabre, Maria; Montero, Miguel A.; Paternain, Jose L.; Romeu, Antoni; (2009). A First-Stage Approximation to Identify New Imprinted Genes through Sequence Analysis of Its Coding Regions. Comparative And Functional Genomics, 2009(549387), 549387-. DOI: 10.1155/2009/549387
    DOI de l'article: 10.1155/2009/549387
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2009
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Biochemistry & Molecular Biology,Biotechnology,Biotechnology & Applied Microbiology,Genetics,Genetics & Heredity,Molecular Biology
    Molecular biology
    Medicina i
    Genetics & heredity
    Genetics
    Biotechnology & applied microbiology
    Biotechnology
    Biodiversidade
    Biochemistry & molecular biology
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