Table of contents for Computational and statistical approaches to genomics / edited by Wei Zhang and Ilya Shmulevich.
Bibliographic record and links to related information available from the Library of Congress catalog
Information from electronic data provided by the publisher. May be incomplete or contain other coding.
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.
Library of Congress subject headings for this publication:
Genomics -- Mathematical models.
Genomics -- Statistical methods.
Genomics -- Data processing.