Graph theory and networks in Biology.
By Oliver Mason, Mark H. A. Verwoerd. IET Systems Biology, 2006
433 citations recorded by the source corpus.
A survey of the use of graph theoretical techniques in Biology is presented. In particular, recent work on identifying and modelling the structure of bio-molecular networks is discussed, as well as the application of centrality measures to interaction networks and research on the hierarchical structure of such networks and network motifs. Work on the link between structural network properties and dynamics is also described, with emphasis on synchronisation and disease propagation.
Subfields: Molecular Biology, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/e764da56e8b4ba6bc21a80ec70b34a8a7b69de59
How researchers see this paper
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In Molecular Biology
- Inanç Birol
- Marco A. Marra
- Francesco Bullo
- Steven J. M. Jones
- Florian Dörfler
- Martin Krzywinski
- Mihai Pop
- Steven L. Salzberg
In Statistical and Nonlinear Physics
Citations in the corpus
- Hive plots - rational approach to visualizing networks (2012, methodology): “Network analysis [18, 19] is complemented by visualization to bridge computation and interpretation, accelerate discovery and deepen in-”
- Graph Information Bottleneck (2020, neutral): “Who may benefit from this research: Graphs have been used to represent a vast amount of real-world data from social science [44], biology [45], geographical mapping [46], finances [47] and recommender systems [48], because of their flexibility in modeling both the relation among the data (structures)…”
- Synchronization in complex networks of phase oscillators: A survey (2014, background): “In some applications, the coupling topology is inherently directed, such as transcriptional, metabolic, or neuronal networks (Mason and Verwoerd, 2007).”