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Computational and Statistical Approaches to Genomics


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Dezember 2007

Beschreibung

Beschreibung

The 2nd edition of this book adds 8 new contributors to reflect a modern cutting edge approach to genomics. The expanded scope includes coverage of statistical issues on single nucleotide polymorphism analysis array, CGH analysis, SAGE analysis, gene shaving and related methods for microarray data analysis, and cross-hybridization issues on oligo arrays. The authors of the 17 original chapters have updated the contents of their chapters, including references, on such topics as the development of novel engineering, statistical and computational principles, as well as methods, models, and tools from these disciplines applied to genomics. TOC:Microarray Image Analysis and Gene Expression Ratio Statistics.- Statistical Considerations in the Assessment of cDNA Microarray Data Obtained Using Amplification.- Sources of Variation in Microarray Experiments.- Studentizing Microarray Data.- Exploratory Clustering of Gene Expression Profiles of Mutated Yeast Strains.- Selecting Informative Genes for Cancer Classification Using Gene Expression Data.- Finding Functional Structures in Glioma Gene-Expressions Using Gene Shaving Clustering and MDL Principle.- Design Issues and Comparison of Methods for Microarray-Based Classification.- Analyzing Protein Sequences Using Signal Analysis Techniques.- Statistical Methods in Serial Analysis of Gene Expression (SAGE).- Normalized Maximum Likelihood Models for Boolean Regression with Application to Prediction and Classification in Genomics.- Inference of Genetic Regulatory Networks.- Regularization and Noise Injection for Improving Genetic Network Models.- Parallel Computation and Visualization Tools for Codetermination Analysis of Multivariate Gene Expression Relations.- Single Nucleotide Polymorphisms and their Applications.- The Contribution of Alternative Transcription and Alternative Splicing to the Complexity of Mammalian Transcriptomes.- Computational Imaging, and Statistical Analysis of Tissue Microarrays.

Inhaltsverzeichnis

Microarray Image Analysis and Gene Expression Ratio Statistics.
Statistical Considerations in the Assessment of cDNA Microarray Data Obtained Using Amplification.
Sources of Variation in Microarray Experiments.
Studentizing Microarray Data.
Exploratory Clustering of Gene Expression Profiles of Mutated Yeast Strains.
Selecting Informative Genes for Cancer Classification Using Gene Expression Data.
Finding Functional Structures in Glioma Gene-Expressions Using Gene Shaving Clustering and MDL Principle.
Design Issues and Comparison of Methods for Microarray-Based Classification.
Analyzing Protein Sequences Using Signal Analysis Techniques.
Statistical Methods in Serial Analysis of Gene Expression (SAGE).
Normalized Maximum Likelihood Models for Boolean Regression with Application to Prediction and Classification in Genomics.
Inference of Genetic Regulatory Networks.
Regularization and Noise Injection for Improving Genetic Network Models.
Parallel Computation and Visualization Tools for Codetermination Analysis of Multivariate Gene Expression Relations.
Single Nucleotide Polymorphisms and their Applications.
The Contribution of Alternative Transcription and Alternative Splicing to the Complexity of Mammalian Transcriptomes.
Computational Imaging, and Statistical Analysis of Tissue Microarrays.

Innenansichten

EAN: 9780387262888
Untertitel: 2nd ed. 2006. Sprache: Englisch. Dateigröße in MByte: 7.
Verlag: Springer US
Erscheinungsdatum: Dezember 2007
Format: pdf eBook
Kopierschutz: Adobe DRM
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