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OverviewBiological systems are extremely complex and have emergent properties that cannot be explained or even predicted by studying their individual parts in isolation. The reductionist approach, although successful in the early days of molecular biology, underestimates this complexity. As the amount of available data grows, so it will become increasingly important to be able to analyse and integrate these large data sets. This book introduces novel approaches and solutions to the Big Data problem in biomedicine, and presents new techniques in the field of graph theory for handling and processing multi-type large data sets. By discussing cutting-edge problems and techniques, researchers from a wide range of fields will be able to gain insights for exploiting big heterogonous data in the life sciences through the concept of 'network of networks'. Full Product DetailsAuthor: Narsis A. Kiani (Karolinska Institutet, Stockholm) , David Gomez-Cabrero (King's College London) , Ginestra Bianconi (Queen Mary University of London)Publisher: Cambridge University Press Imprint: Cambridge University Press Dimensions: Width: 17.50cm , Height: 1.50cm , Length: 25.00cm Weight: 0.550kg ISBN: 9781108428873ISBN 10: 1108428878 Pages: 214 Publication Date: 01 April 2021 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In stock  We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsPreface; 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.Reviews'… Networks of Networks in Biology should be of interest and a good introductory resource for molecular biologists, cell biologists, and biochemists, as well as bioinformaticians not yet acquainted with multilayer networks.' Ingo Brigandt, Quarterly Review of Biology Author InformationNarsis A. Kiani is Assistant Professor and the Co-leader of Algorithmic Dynamics in the Department of Oncology-Pathology of the Karolinska Institutet, Sweden. She is passionate about mathematics and is interested in the fundamental question of what observations about the effects at the microscopic level can tell us about the macroscopic nature of biological systems and vice versa, and how defects and disorder affect these systems. David Gomez-Cabrero is the Head of the Translational Bioinformatics Unit at Navarrabiomed, Spain. Since 2009, he has specialised in bioinformatics and data integration analysis, first as a post-doctorate and subsequently as Assistant Professor at the Karolinska Institutet, Sweden, and as Senior Lecturer at King's College London, UK. He collaborates with clinical groups that investigate multiple sclerosis, rheumatoid arthritis, chronic obstructive pulmonary disease (COPD) and cancer, among other diseases. Ginestra Bianconi is Professor of Applied Mathematics at Queen Mary University of London and a Turing Fellow at the Alan Turing Institute. She is Editor-in-Chief of the Journal of Physics: Complexity and Editor of Scientific Reports, PloS One. She has published more than 150 articles in network theory and interdisciplinary applications. She has authored the book Multilayer Networks: Structure and Function (2018). Tab Content 6Author Website:Countries AvailableAll regions |
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