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DNA Microarrays, Part B: Databases and Statistics

Alan Kimmel and Brian Oliver  Edited by Alan Kimmel and Brian Oliver 
Academic Press  September 2006  



hardback  512 pp  ISBN 9780121828165      £115.00
See also Part A

  • Provides an overview of platforms
  • Includes experimental design and wet bench protocols
  • Presents statistical and data analysis methods, array databases, data visualization and meta analysis

Modern DNA microarray technologies have evolved over the past 25 years to the point where it is now possible to take many million measurements from a single experiment. These two volumes, Parts A & B in the Methods in Enzymology series provide methods that will shepard any molecular biologist through the process of planning, performing, and publishing microarray results.

Part A starts with an overview of a number of microarray platforms, both commercial and academically produced and includes wet bench protocols for performing traditional expression analysis and derivative techniques such as detection of transcription factor occupancy and chromatin status. Wet-bench protocols and troubleshooting techniques continue into Part B. These techniques are well rooted in traditional molecular biology and while they require traditional care, a researcher that can r eproducibly generate beautiful Northern or Southern blots should have no difficulty generating beautiful array hybridizations.

Data management is a more recent problem for most biologists. The bulk of Part B provides a range of techniques for data handling. This includes critical issues, from normalization within and between arrays, to uploading your results to the public repositories for array data, and how to integrate data from multiple sources. There are chapters in Part B for both the debutant and the expert bioinformatician.

Of interest to biochemists and related researchers working with DNA microarray technologies.

Contents

  • The Use of External Controls in Microarray Experiments.
  • Standards in gene expression microarray experiments.
  • Scanning Microarrays: Current Methods and Future Directions.
  • BioArray software environment.
  • Bioconductor: An open source framework for bioinformatics and computational biology.
  • TM4 microarray software suite.
  • Clustering microarray data.
  • Analysis of variance of microarray data.
  • Microarray quality control.
  • Principle component and ANOVA analysis of array data using Partek€ Genomics SolutionTM.
  • Statistics for ChIP-chip and DNase hypersensitivity experiments on NimbleGen arrays.
  • Extrapolating traditional DNA microarray statistics to the tiling and protein microarray technologies.
  • Random dataset generation to support microarray analysis.
  • Using ontologies to annotate microarray experiments
  • Interpreting experimental results using gene ontologies.
  • Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval and analysis.
  • Data storage and analysis in ArrayExpress.
  • Clustering methods for analyzing large datasets: gonad development, a study case.
  • GeneSprings.
  • Visualizing networks.
  • Random forests for array data.
  • Hybridization troubleshooting.
  • RNA extraction and handling for microarray analysis.
  • Analyzing MicroRNA expression using microarrays.
To find similar publications, click on a keyword below:
Academic Press : DNA : analytical methods : biochemistry : biotechnology : databases : microarrays : statistics

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