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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.




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.




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.


Content:
Front Matter....Pages i-xiii
Data Mining of Malaria Parasite Gene Expression for Possible Translational Research....Pages 1-10
Constructing Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals of the Intraerythrocytic Development Cycle....Pages 11-26
Simple Methods for Peak and Valley Detection in Time Series Microarray Data....Pages 27-44
Oxidative Stress Genes in Plasmodium falciparum as Indicated by Temporal Gene Expression....Pages 45-58
Identifying Stage-Specific Genes by Combining Information from Two Different Types of Oligonucleotide Arrays....Pages 59-74
Construction of Malaria Gene Expression Network Using Partial Correlations....Pages 75-88
Detecting Network Motifs in Gene Co-expression Networks Through Integration of Protein Domain Information....Pages 89-102
Chromosomal Clustering of Periodically Expressed Genes in Plasmodium falciparum ....Pages 103-119
PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum ....Pages 121-136
Linking Gene Expression Patterns and Transcriptional Regulation in Plasmodium falciparum ....Pages 137-156
Chromosomal Spatial Correlation of Gene Expression in Plasmodium falciparum ....Pages 157-171
Back Matter....Pages 173-175


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.


Content:
Front Matter....Pages i-xiii
Data Mining of Malaria Parasite Gene Expression for Possible Translational Research....Pages 1-10
Constructing Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals of the Intraerythrocytic Development Cycle....Pages 11-26
Simple Methods for Peak and Valley Detection in Time Series Microarray Data....Pages 27-44
Oxidative Stress Genes in Plasmodium falciparum as Indicated by Temporal Gene Expression....Pages 45-58
Identifying Stage-Specific Genes by Combining Information from Two Different Types of Oligonucleotide Arrays....Pages 59-74
Construction of Malaria Gene Expression Network Using Partial Correlations....Pages 75-88
Detecting Network Motifs in Gene Co-expression Networks Through Integration of Protein Domain Information....Pages 89-102
Chromosomal Clustering of Periodically Expressed Genes in Plasmodium falciparum ....Pages 103-119
PlasmoTFBM: An Intelligent Queriable Database for Predicted Transcription Factor Binding Motifs in Plasmodium falciparum ....Pages 121-136
Linking Gene Expression Patterns and Transcriptional Regulation in Plasmodium falciparum ....Pages 137-156
Chromosomal Spatial Correlation of Gene Expression in Plasmodium falciparum ....Pages 157-171
Back Matter....Pages 173-175
....
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