A Markov chain approach to randomly grown graphs
type: Item
instance of: scholarly article
title: A Markov chain approach to randomly grown graphs
zbMATH Open document ID: 1146.05311
DOI: 10.1155/2008/190836
author: Michael Knudsen
author: Carsten Wiuf
published in: Journal of Applied Mathematics
publication date: 2008-08-15T00:00:00Z
full work available at URL: https://eudml.org/doc/54519
review text: Summary: A Markov chain approach to the study of randomly grown graphs is proposed and applied to some popular models that have found use in biology and elsewhere. For most randomly grown graphs used in biology, it is not known whether the graph or properties of the graph converge (in some sense) as the number of vertices becomes large. Particularly, we study the behaviour of the degree sequence, that is, the number of vertices with degree \(0,1,\dots ,\) in large graphs, and apply our results to the partial duplication model. We further illustrate the results by application to real data.
Mathematics Subject Classification ID: 05C80
Mathematics Subject Classification ID: 05C07
Mathematics Subject Classification ID: 05C90
Mathematics Subject Classification ID: 60C05
Mathematics Subject Classification ID: 60J10
Mathematics Subject Classification ID: 92B05
zbMATH DE Number: 5312415
zbMATH Keywords: Markov chain approach
zbMATH Keywords: randomly grown graphs
zbMATH Keywords: biology
zbMATH Keywords: partial duplication model
Wikidata QID: Q58645953
MaRDI profile type: Publication
OpenAlex ID: W1997448075
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DBLP publication ID: journals/jam/KnudsenW08
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description: scientific article; zbMATH DE number 5312415