Statistical approach study microarray di bhatt drushti (3 risultati)

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    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2012

      3659133418 / 9783659133411

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      Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books

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      Condizione: Usato - Come nuovo

      EUR 121,39

      EUR 29,17 spedizione 
      Spedito da Regno Unito a U.S.A.

      Quantità: 1 disponibili

      Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2012

      3659133418 / 9783659133411

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      • Print on Demand

      Da: moluna, Greven, Germaniamoluna

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      Condizione: Nuovo

      EUR 41,67

      EUR 48,99 spedizione 
      Spedito da Germania a U.S.A.

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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bhatt DrushtiPursuing M.Phil Bioinformatics from Gujarat University, Ahmedabad, India. Completed research work on Microarray data analysis using R Language. Presently working on the project miRNA(microRNA), targeting to treat disease.

    • Lingua: Inglese

      Editore: LAP Lambert Academic Publishing, 2012

      3659133418 / 9783659133411

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      EUR 70,99

      EUR 30,50 spedizione 
      Spedito da Germania a U.S.A.

      Quantità: 2 disponibili

      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Microarray is a novel technology to identify gene expression of thousands of genes simultaneously. This work is attempted to perform microarray data analyses to determine differential gene expression using the open-source R programming environment in conjunction with the open-source Bioconductor software.We describe procedures for analysis of data using box plots and recommended procedures from Affymetrix for quality control are discussed. The Robust Multichip Averaging (RMA) and MAS5 procedure was used for background correction, normalization and summarization of the AffyBatch probe-level data to obtain expression level data and to discover differentially expressed genes. Heatmaps are used to demonstrate over and under expressed genes in conjunction with t-statistics for determining interesting genes while pFDR was performed to remove false negative. We showed, with real data, how implementation of functions in R and Bioconductor successfully identified differentially expressed genes that may play a role in obesity.