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Applied statistics for network biology: methods in systems biology
2011, Wiley-Blackwell
in English
3527327509 9783527327508
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Table of Contents
Pt. One. Modeling, simulation, and meaning of gene networks: 1. Network analysis to interpret complex phenotypes
2. Stochastic modeling of gene regulatory networks
3. Modeling expression quantitative trait loci in multiple populations
Pt. Two. Inference of gene networks: 4. Transcriptional network inference based on information theory
5. Elucidation of general and condition-dependent gene pathways using mixture models and bayesian networks
6. Multiscale network reconstruction from gene expression measurements: correlations, perturbations, and "A Priori Biological Knowledge"
7. Gene regulatory networks inference: combining a genetic programming and H [infinity symbol] filtering approach
8. Computational reconstruction of protein interaction networks
Pt. Three. Analysis of gene networks: 9. What if the fit is unfit? Criteria for biological systems estimation beyond residual errors
10. Machine learning methods for identifying essential genes and proteins in networks
11. Gene coexpression networks for the analysis of DNA microarray data
12. Correlation network analysis and knowledge integration
13. Network screening: a new method to identify active networks from an ensemble of known networks
14. Community detection in biological networks
15. On some inverse problems in generating probabilistic boolean networks
16. Boolean analysis of gene expression datasets
Pt. Four. Systems approach to diseases: 17. Representing cancer cell trajectories in a phase-space diagram: switching cellular states by biological phase transitions
18. Protein network analysis for disease gene identification and prioritization
19. Pathways and networks as functional descriptors for human disease and drug response endpoints.
Edition Notes
Includes bibliographical references and index.
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- Created February 8, 2012
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January 5, 2023 | Edited by MARC Bot | import existing book |
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