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by Patrick McConnell (Editor), Simon Lin (Editor), Patrick Hurban (Editor)
As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments. The Critical Assessment of Microarray Data Analysis (CAMDA) conference was the first to establish a forum for a cross section of researchers to examine a common data set and apply innovative analytical techniques to microarray data. Methods of Microarray Analysis V includes selected papers from CAMDA'04, and focuses on data sets relating to a significant global health issue, malaria. The contributions come from research in such fields as statistics, biology, computer science and mathematics. The book also presents review papers, which provide a more general look at various analytical approaches, as well as background readings for the advanced topics discussed. Previous volumes in the series focus on classification (v. I), pattern recognition (v. II), quality control issues (v. III), and associating array data with a survival endpoint, lung cancer, (v. IV).
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Since the inception of microarrays, studies in this field have drastically evolved with analysis methods needing to advance in-step. The CAMDA conference plays a role in this ever-changing discipline by providing a forum in which investigators can analyze the same datasets using different methods.
Methods of Microarray Data Analysis V is the fifth book in this series, and focuses on the important issue of analyzing array data in a time series with correlating biological data. Previous books in this series focused on classification (Volume I), pattern recognition (Volume II), quality control issues (Volume III), and survival analysis (Volume IV).
In this volume, all investigators analyzed a single dataset on the lifecycle of the most deadly of malaria parasites, Plasmodium falciparum. The emphasis this year is on the application of novel and existing computational methodologies towards infectious disease. We highlight an introductory chapter by Raphael D. Isokpehi, a leading expert in the field of malaria. Ten of the papers presented at the conference are included, which range from the inference of genetic networks to the analysis of the spatial correlation of array data. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state-of-the-art in microarray data analysis.
Patrick McConnell is a researcher in the Duke Bioinformatics Group in the Duke Comprehensive Cancer Center.
Simon M. Lin is a faculty member in the Robert H. Lurie Comprehensive Cancer Center and associate director of Bioinformatics at Northwestern University.
Patrick Hurban is director of Investigational Genomics at Icoria, Inc., a Clinical Data company.
