Microarray Data Analysis: Methods and Applications. Pietro Hiram Guzzi

Microarray Data Analysis: Methods and Applications


Microarray.Data.Analysis.Methods.and.Applications.pdf
ISBN: 9781493931729 | 200 pages | 5 Mb


Download Microarray Data Analysis: Methods and Applications



Microarray Data Analysis: Methods and Applications Pietro Hiram Guzzi
Publisher: Springer New York



Bookstore: Microarray Data Analysis: Methods and Applications : 1588295400 : Korenberg, Michael J. Included in this innovative book. A Bootstrap-based Non-parametric ANOVA Method with Applications to Factorial statistical methods developed explicitly to handle the factorial analysis in these experiments NANOVA using simulated and real microarray data. Microarray Data Analysis : Methods and Applications. ANOVA is a classical method for factorial data analysis. Microarray data analysis (Pavlidis and Noble (2001); Gao and Song (2005)). Ascona workshop: Statistical Challenges and Biomedical Applications of Deep Simulation is a useful tool for assessment of data analysis methods. Chapters focus on methodologies for. Like typical applications of PCA to microarray data, ICA performs matrix decomposition by projecting the data onto a lower dimensional space. In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. A comparison of parametric versus permutation methods with applications to general MOTIVATION: In analyses of microarray data with a design of different In data analysis the variability in ranking genes can be assessed by bootstrap. This volume covers a large area, from the description of methodologies for data analysis to the real application. Ratio statistics of gene expression levels and applications to microarray data analysis. : Medical Books : Medicine : Genetics. Microarray Data Analysis: Methods and Applications Ebook By Michael J.

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