Methods of Microarray Data Analysis V [electronic resource] /
CAMDA (Conference)(5th :2004)
McConnell, Patrick.editor.
Lin, Simon.editor.
Hurban, Patrick.editor.
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.
"... Critical Assessment of Microarray Data Analysis (CAMDA) Conference, with the fifth edition taking place during November 2004"---Introd.
Includes bibliographical references and index.
Data Mining of Malaria Parasite Gene Expression for Possible Translational Research -- Constructing Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals of the Intraerythrocytic Development Cycle -- Simple Methods for Peak and Valley Detection in Time Series Microarray Data -- Oxidative Stress Genes in Plasmodium falciparum as Indicated by Temporal Gene Expression -- Identifying Stage-Specific Genes by Combining Information from Two Different Types of Oligonucleotide Arrays -- Construction of Malaria Gene Expression Network Using Partial Correlations -- Detecting Network Motifs in Gene Co-expression Networks Through Integration of Protein Domain Information -- Chromosomal Clustering of Periodically Expressed Genes in Plasmodium falciparum -- PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum -- Linking Gene Expression Patterns and Transcriptional Regulation in Plasmodium falciparum -- Chromosomal Spatial Correlation of Gene Expression in Plasmodium falciparum.
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.
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Biomathematics.
Biochemistry, general.
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Human Genetics.
Proteomics.
Statistics for Life Sciences, Medicine, Health Sciences.
Mathematical and Computational Biology.