The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.

The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.

MODELING, SIMULATION AND MEANING OF GENE NETWORKSNetwork Analysis to Interpret Complex Phenotypes (Hong Yu, Jialiang Huang, Wei Zhang, and Jing-Dong J. Han)Stochastic Modelling of Regulatory Networks (Tianhai Tian)Modeling eQTL in Multiple Populations (Ching-Lin Hsiao and Cathy S.J. Fann)INFERENCE OF GENE NETWORKSTranscriptional Network Inference based on Information Theory (Patrick E. Meyer and Gianluca Bontempi)Elucidation of General and Condition-dependent Gene Pathways Using Mixture Models and Bayesian Networks (Sandra Rodriguez-Zas and Younhee Ko)Multi-scale Networks Reconstruction from Gene-expression Measurements: Correlations, Perturbations and a-priori Biological Knowledge (Daniel Remondini and Gastone Castellani)Gene Regulatory Network Inference: Combining a Genetic Programming and Hendless Filtering Approach (Lijun Qian, Haixin Wang, and Xiangfang Li)Computational Reconstruction of Protein Interaction Networks (Konrad Mönks, Irmgard Mühlberger, Andreas Bernthaler, Raul Fechete, Paul Perco, Rudolf Freund, Arno Lukas, and Bernd Mayer)ANALYSIS OF GENE NETWORKSWhat if the Fit is Unfit? Criteria for Biological Systems Estimation Beyond Residual Errors (Eberhard O. Voit)Machine Learning Methods for Identifying Essential Genes and Proteins in Networks (Kitiporn Plaimas and Rainer König)Gene Co-expression Networks for the Analysis of DNA Microarray Data (Matthew Weirauch)Correlation Network Analysis and Knowledge Integration (Thomas N. Plasterer, Robert Stanley, and Erich Gombocz)Network Screening: A New Method to Identify Active Networks from an Ensemble of Known Networks (Shigeru Saito and Katsuhisa Horimoto)Community Detection in Biological Networks (Gautam S. Thakur)On Some Inverse Problems in Generating Probabilistic Boolean Networks (Xi Chen, Wai-Ki Ching and Nam-Kiu Tsing)Boolean analysis of gene-expression datasets (Debashis Sahoo)SYSTEMS APPROACH TO DISEASESRepresenting Cancer Cell Trajectories in a Phase-space Diagram: Switching Cellular States by Biological Phase Transitions (Mariano Bizzarri and Alessandro Giuliani)Protein Network Analysis for Disease Gene Identification and Prioritization (Jing Chen and Anil G. Jegga)Pathways and Networks as Functional Descriptors for Human Disease and Drug Response Endpoints (Y. Nikolsky and B. Bessarabova and E. Kirillov and Z. Dezso and W. Nikolskaya)