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Networks in Cell Biology
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  • Cited by 12
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Ferreira, Gustavo Rodrigues Nakaya, Helder Imoto and Costa, Luciano da Fontoura 2018. Gene regulatory and signaling networks exhibit distinct topological distributions of motifs. Physical Review E, Vol. 97, Issue. 4,

    Muñoz, Miguel A. 2018. Colloquium : Criticality and dynamical scaling in living systems. Reviews of Modern Physics, Vol. 90, Issue. 3,

    García-Calvo, Raúl Guisado, JL Diaz-del-Rio, Fernando Córdoba, Antonio and Jiménez-Morales, Francisco 2018. Graphics Processing Unit–Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks. Evolutionary Bioinformatics, Vol. 14, Issue. , p. 117693431876788.

    Villegas, Pablo Ruiz-Franco, José Hidalgo, Jorge and Muñoz, Miguel A. 2016. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks. Scientific Reports, Vol. 6, Issue. 1,

    Grabow, Carsten Grosskinsky, Stefan Kurths, Jürgen and Timme, Marc 2015. Collective relaxation dynamics of small-world networks. Physical Review E, Vol. 91, Issue. 5,

    Cerina, Federica Zhu, Zhen Chessa, Alessandro Riccaboni, Massimo and Sendina-Nadal, Irene 2015. World Input-Output Network. PLOS ONE, Vol. 10, Issue. 7, p. e0134025.

    Pearcy, Nicole Crofts, Jonathan J. and Chuzhanova, Nadia 2015. Network motif frequency vectors reveal evolving metabolic network organisation. Molecular BioSystems, Vol. 11, Issue. 1, p. 77.

    Zhu, Zhen Cerina, Federica Chessa, Alessandro Caldarelli, Guido Riccaboni, Massimo and Perc, Matjaz 2014. The Rise of China in the International Trade Network: A Community Core Detection Approach. PLoS ONE, Vol. 9, Issue. 8, p. e105496.

    Crofts, Jonathan J. and Estrada, Ernesto 2014. A statistical mechanics description of environmental variability in metabolic networks. Journal of Mathematical Chemistry, Vol. 52, Issue. 2, p. 675.

    Albergante, Luca Blow, J Julian and Newman, Timothy J 2014. Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks. eLife, Vol. 3, Issue. ,

    Barra, Adriano and Agliari, Elena 2011. Equilibrium statistical mechanics on correlated random graphs. Journal of Statistical Mechanics: Theory and Experiment, Vol. 2011, Issue. 02, p. P02027.

    Campbell, Colin Thakar, Juilee and Albert, Réka 2011. Network analysis reveals cross-links of the immune pathways activated by bacteria and allergen. Physical Review E, Vol. 84, Issue. 3,

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Book description

The science of complex biological networks is transforming research in areas ranging from evolutionary biology to medicine. This is the first book on the subject, providing a comprehensive introduction to complex network science and its biological applications. With contributions from key leaders in both network theory and modern cell biology, this book discusses the network science that is increasingly foundational for systems biology and the quantitative understanding of living systems. It surveys studies in the quantitative structure and dynamics of genetic regulatory networks, molecular networks underlying cellular metabolism, and other fundamental biological processes. The book balances empirical studies and theory to give a unified overview of this interdisciplinary science. It is a key introductory text for graduate students and researchers in physics, biology and biochemistry, and presents ideas and techniques from fields outside the reader's own area of specialization.

Reviews

'Network science has experienced a spectacular explosion in the past decade, influencing a wide range of fields, from computer science to sociology. Yet, nowhere is the impact of the new theoretical framework as promising as it is in cell biology - many of the difficult open questions cannot be understood without a network based approach. Networks in Cell Biology offers an excellent introduction to this frontier, at the same time capturing the current state of research. With contributions from the best in the field, it is a valuable addition to the shelf of anyone interested in this exciting area.'

Albert-László Barabási - Northeastern University and Harvard Medical School

'This book describes the state of the art in understanding cellular networks through contributions by leaders in modern cell biology and network theory. It is clearly organized and exhibits an excellent balance between empirical studies and theory. The biological underpinnings are explained clearly and comprehensively, and the appendices give a great primer to the key mathematical concepts necessary for network analysis and modeling. This book will be of great use as a course textbook or for self-study.'

Reka Albert - Pennsylvania State University

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