DNA Microarrays and Related Genomics Techniques
Design, Analysis, and Interpretation of Experiments
Erschienen am 14. November 2005
392 Seiten
978-1-4200-2879-9 (ISBN)
Beschreibung
Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches
Weitere Details
Sprache
Englisch
Verlagsort
London
Großbritannien
Verlagsgruppe
Taylor & Francis Ltd
Zielgruppe
Für Beruf und Forschung
Researchers and methodologists studying microarray data, biostatistics, genomics, proteomics, and other genetic statistical data.
Illustrationen
18 s/w Tabellen
18 tables and 223 equations
Dateigröße
9,47 MB
ISBN-13
978-1-4200-2879-9 (9781420028799)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Weitere Ausgaben
Andere Ausgaben
David B. Allison | Grier P. Page | T. Mark Beasley
DNA Microarrays and Related Genomics Techniques
Design, Analysis, and Interpretation of Experiments
Buch
10/2019
1. Auflage
Chapman & Hall/CRC
96,40 €
Versand in 15-20 Tagen
David B. Allison | Grier P. Page | T. Mark Beasley
DNA Microarrays and Related Genomics Techniques
Design, Analysis, and Interpretation of Experiments
Buch
11/2005
1. Auflage
Taylor & Francis
208,70 €
Versand in 15-20 Tagen
Personen
David B. Allison, Grier P. Page, T. Mark Beasley, Jode W. Edwards
Inhalt
Microarray Platforms and Blood Samples. Normalization of Microarray Data. Microarray Quality Control and Assessment. Epistemological Foundations of Statistical Methods for High-Dimensional Biology. The Role of Sample Size on Measures of Uncertainty and Power. Pooling Biological Samples in Microarray Experiments. Designing Microarrays for the Analysis of Gene Expressions. Overview of Standard Clustering Approaches for Gene Microarray Data Analysis. Cluster Stability. Dimensionality Reduction and Discrimination. Modeling Affymetrix Data at the Probe Level. Parametric Linear Models. The Use of Nonparametric Procedures in the Statistical Analysis of Microarray Data. Bayesian Analysis of Microarray Data. False Discovery Rate and Multiple Comparison Procedures. Using Standards to Facilitate Interoperation of Heterogeneous Microarray Databases and Analytic Tools. Post-Analysis Interpretation: What Do I Do with This Gene List? Combining High Dimensional Biological Data to Study Complex Diseases and Quantitative Traits.
