Networks of Networks in Biology: Concepts, Tools and Applications
Editat de Narsis A. Kiani, David Gomez-Cabrero, Ginestra Bianconien Limba Engleză Hardback – 31 mar 2021
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Specificații
ISBN-13: 9781108428873
ISBN-10: 1108428878
Pagini: 214
Dimensiuni: 175 x 250 x 15 mm
Greutate: 0.54 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:Cambridge, United Kingdom
ISBN-10: 1108428878
Pagini: 214
Dimensiuni: 175 x 250 x 15 mm
Greutate: 0.54 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:Cambridge, United Kingdom
Cuprins
Preface; Part I. Networks in Biology: 1. An Introduction to Biological Networks Nuria Planell, Xabier Martinez de Morentin and David Gomez-Cabrero; 2. Graph Theory Akram Dehnokhalaji and Nasim Nasrabadi; Part II. Network Analysis: 3. Structural Analysis of Biological Networks Narsis A. Kiani and Mikko Kivelä; 4. Networks From an Information-Theoretic and Algorithmic Complexity Perspective Hector Zenil and Narsis A. Kiani; 5. Integration and Feature Identification in Multi-layer Network using a Heat Diffusion Approach Gordon Ball and Jesper Tegnér; Part III. Multi-layer Networks: 6. Large Multiplex Networks Ginestra Bianconi; 7. Large Existing Tools for Analysis of Multilayer Networks Manlio De Domenico and Massimo Stella; 8. Large Dynamics on Multilayer Networks Manlio De Domenico and Massimo Stella; Part IV. Applications: 9. The Network of Networks Involved in Human Disease Celine Sin and Jörg Menche; 10. Towards a Multi-Layer Network Analysis of Disease: Challenges and Opportunities Through the Lens of Multiple Sclerosis Jesper Tegnér, Ingrid Kockum, Mika Gustafsson and David Gomez-Cabrero; 11. Microbiome: A Multi-Layer Network View Is Required Rodrigo Bacigalupe, Saeed Shoai and David Gomez-Cabrero; Part V. Conclusion : Concluding Remarks: Open Questions and Challenges Ginestra Bianconi, David Gomez-Cabrero, Jesper Tegnér and Narsis A. Kiani; Index.
Descriere
Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.