 |
Computational systems biology / edited by Jason McDermott ... [et al.]. — Totowa, N.J. : Humana, c2009. – (58.17/M592/v.541) |
Contents
Contents
Preface
Contributors
Color Plates
PART I: NETWORK COMPONENTS
l. Identification of cis-Regulatory Elements in Gene Co-expression Networks
Using A-GLAM
2. Structure-Based Ab Initio Prediction of Transcription Factor-Binding Sites
3. Inferring Protein-Protein Interactions from Multiple Protein Domain Combinations
4. Prediction of Protein-Protein Interactions: A Study of the Co-evolution Model
5. Computational Reconstruction of Protein-Protein Interaction Networks: Algorithms and Issues
6. Prediction and Integration of Regulatory and Protein-Protein Interactions 101
7. Detecting Hierarchical Modularity in Biological Networks
PART II: NETWORK INFERENCE
8. Methods to Reconstruct and Compare Transcriptional Regulatory Networks 163
9. Learning Global Models of Transcriptional Regulatory Networks from Data 181
10. Inferring Molecular Interactions Pathways from eQTL Data
l1. Methods for the Inference of Biological Pathways and Networks
PART III: NETWORK DYNAMICS
12. Exploring Pathways from Gene Co-expression to Network Dynamics 249
13. Network Dynamics
14. Kinetic Modeling of Biological Systems
15. Guidance for Data Collection and Computational Modelling of Regulatory Networks 337
PART IV: FUNCTION AND EVOLUTIONARY SYSTEMS BIOLOGY
16. A Maximum Likelihood Method for Reconstruction of the Evolution of Eukaryotic Gene Structure
17. Enzyme Function Prediction with Interpretable Models
18. Using Evolutionary Information to Find Specificity-Determining and Co-evolving Residues
19. Connecting Protein Interaction Data， Mutations， and Disease Using Bioinformatics
20. Effects of Functional Bias on Supervised Learning ofa Gene Network Model 463
PART V: COMPUTATIONAL INFRASTRUCTURE FOR SYSTEMS BIOLOGY
21. Comparing Algorithms for Clustering of Expression Data: How to Assess Gene Clusters 479
22. The Bioverse API and Web Application
23. Computational Representation of Biological Systems
24. Biological Network Inference and Analysis Using SEBINI and CABIN
Index
