Quantitative and Network Biology / Analysis of Microarray Data
A Network-Based Approach
(Sprache: Englisch)
This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents:* Understanding and Preprocessing Microarray Data*...
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Klappentext zu „Quantitative and Network Biology / Analysis of Microarray Data “
This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents:* Understanding and Preprocessing Microarray Data* Clustering of Microarray Data* Reconstruction of the Yeast Cell Cycle by Partial Correlations of Higher Order* Bilayer Verification Algorithm* Probabilistic Boolean Networks as Models for Gene Regulation* Estimating Transcriptional Regulatory Networks by a Bayesian Network* Analysis of Therapeutic Compound Effects* Statistical Methods for Inference of Genetic Networks and Regulatory Modules* Identification of Genetic Networks by Structural Equations* Predicting Functional Modules Using Microarray and Protein Interaction Data* Integrating Results from Literature Mining and Microarray Experiments to Infer Gene NetworksThe book is for both, scientists using the technique as well as those developing new analysis techniques.
Inhaltsverzeichnis zu „Quantitative and Network Biology / Analysis of Microarray Data “
Introduction to DNA MicroarraysComparative Analysis of Clustering Methods for Microarray DataFinding Verified Edges in Genetic/Gene Networks: Bilayer Verification for Network Recovery in the PresenceComputational Inference of Biological Causal Networks - Analysis of Therapeutic Compound EffectsReverse Engineering Gene Regulatory Networks with Various Machine Learning MethodsStatistical Methods for Inference of Genetic Networks and Regulatory ModulesA Model of Genetic Networks with Delayed Stochastic DynamicsProbabilistic Boolean Networks as Models for Gene RegulationStructural Equation for Identification of Genetic NetworksDetecting Pathological Pathways of a Complex Disease by a Comparative Analysis of NetworksPredicting Functional Modules Using Microarray and Protein Interaction DataComputational Reconstruction of Transcriptional Regulatory Modules of the Yeast Cell CyclePathway-Based Methods for Analyzing Microarray DataThe Most Probable Genetic Interaction Networks Inferred from Gene Expression Patterns
Autoren-Porträt
Matthias Dehmer studied mathematics at the University of Siegen, Germany, and received his PhD in Computer Science from the Technical University of Darmstadt, Germany. Currently he is a postdoctoral research associate at the University of Rostock, Germany, in the Department of Bioinformatics and Systems Biology.Frank Emmert-Streib studied physics at the University of Siegen, Germany, and received his PhD in Theoretical Physics from the University of Bremen, Germany. He is currently a postdoctoral research associate at the Stowers Institute for Medical Research, Kansas City, USA, in the Department of Bioinformatics.
Bibliographische Angaben
- 2008, XX, 418 Seiten, 29 farbige Abbildungen, 98 Schwarz-Weiß-Abbildungen, Maße: 17,9 x 24,7 cm, Gebunden, Englisch
- Herausgegeben: Frank Emmert-Streib, Matthias Dehmer
- Verlag: Wiley-VCH
- ISBN-10: 3527318224
- ISBN-13: 9783527318223
- Erscheinungsdatum: 13.02.2008
Sprache:
Englisch
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