Gene Regulatory Networks: Methods and Protocols (Hardcover, 2019)

Preface... Table of Contents... Contributing Authors... 1. Gene Regulatory Network Inference: An Introductory Survey Van Anh Huynh-Thu and Guido Sanguinetti 2. Statistical Network Inference for Time-Varying Molecular Data with Dynamic Bayesian Networks Frank Dondelinger and Sach Mukherjee 3. Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series Data Marco Grzegorczyk, Andrej Aderhold, and Dirk Husmeier 4. Whole-Transcriptome Causal Network Inference with Genomic and Transcriptomic Data Lingfei Wang and Tom Michoel 5. Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks Alex White and Matthieu Vignes 6. A Multiattribute Gaussian Graphical Model for Inferring Multiscale Regulatory Networks: An Application in Breast Cancer Julien Chiquet, Guillem Rigaill, and Martina Sundqvist 7. Integrative Approaches for Inference of Genome-Scale Gene Regulatory Networks Alireza Fotuhi Siahpirani, Deborah Chasman, and Sushmita Roy 8. Unsupervised Gene Network Inference with Decision Trees and Random Forests Van Anh Huynh-Thu and Pierre Geurts 9. Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3 Van Anh Huynh-Thu and Guido Sanguinetti 10. Network Inference from Single-Cell Transcriptomic Data Helena Todorov, Robrecht Cannoodt, Wouter Saelens, and Yvan Saeys 11. Inferring Gene Regulatory Networks from Multiple Datasets Christopher A. Penfold, Iulia Gherman, Anastasiya Sybirna, and David L. Wild 12. Unsupervised GRN Ensemble Pau Bellot, Philippe Salembier, Ngoc C. Pham, and Patrick E. Meyer 13. Learning Differential Module Networks across Multiple Experimental Conditions Pau Erola, Eric Bonnet, and Tom Michoel 14. Stability in GRN Inference Giuseppe Jurman, Michele Filosi, Roberto Visintainer, Samantha Riccadonna, and Cesare Furlanello 15. Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling Olivia Angelin-Bonnet, Patrick J. Biggs, and Matthieu Vignes 16. Scalable Inference of Ordinary Differential Equation Models of Biochemical Processes Fabian Frohlich, Carolin Loos, and Jan Hasenauer