Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks
By Dirk Koschützki, Falk Schreiber. Gene Regulation and Systems Biology, 2008
344 citations recorded by the source corpus.
The structural analysis of biological networks includes the ranking of the vertices based on the connection structure of a network. To support this analysis we discuss centrality measures which indicate the importance of vertices, and demonstrate their applicability on a gene regulatory network. We show that common centrality measures result in different valuations of the vertices and that novel measures tailored to specific biological investigations are useful for the analysis of biological networks, in particular gene regulatory networks.
Subfields: Computational Theory and Mathematics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/4240f710ae528e807a1ea3dace61ac6e47c3b516
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
In Molecular Biology
Citations in the corpus
- Study on centrality measures in social networks: a survey (2018, background): “Shaw (1954) first introduced degree centrality as an index of important vertex and hence defined by Nieminen (1974). Freeman (1978) first developed a mathematical model for centrality which is based on the links connected to a vertex.”
- Betweenness Centrality in Some Classes of Graphs (2014, background): “Betweenness centrality plays an important role in analysis of social networks [21, 22], computer networks [16] and many other types of network data models [7, 11, 15, 17, 19, 23].”