A Markov chain approach to randomly grown graphs

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

A Markov chain approach to randomly grown graphs. / Knudsen, Michael; Wiuf, Carsten.

In: Journal of Applied Mathematics, Vol. 2008, 190836, 09.07.2008.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Knudsen, M & Wiuf, C 2008, 'A Markov chain approach to randomly grown graphs', Journal of Applied Mathematics, vol. 2008, 190836. https://doi.org/10.1155/2008/190836

APA

Knudsen, M., & Wiuf, C. (2008). A Markov chain approach to randomly grown graphs. Journal of Applied Mathematics, 2008, [190836]. https://doi.org/10.1155/2008/190836

Vancouver

Knudsen M, Wiuf C. A Markov chain approach to randomly grown graphs. Journal of Applied Mathematics. 2008 Jul 9;2008. 190836. https://doi.org/10.1155/2008/190836

Author

Knudsen, Michael ; Wiuf, Carsten. / A Markov chain approach to randomly grown graphs. In: Journal of Applied Mathematics. 2008 ; Vol. 2008.

Bibtex

@article{912199bc296a4b3199cac65b18898ed3,
title = "A Markov chain approach to randomly grown graphs",
abstract = "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 else where. 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,..., in large graphs, and apply our results to the partial duplication model. We further illustrate the results by application to real data.",
author = "Michael Knudsen and Carsten Wiuf",
year = "2008",
month = jul,
day = "9",
doi = "10.1155/2008/190836",
language = "English",
volume = "2008",
journal = "Journal of Applied Mathematics",
issn = "1110-757X",
publisher = "Hindawi Publishing Corporation",

}

RIS

TY - JOUR

T1 - A Markov chain approach to randomly grown graphs

AU - Knudsen, Michael

AU - Wiuf, Carsten

PY - 2008/7/9

Y1 - 2008/7/9

N2 - 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 else where. 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,..., in large graphs, and apply our results to the partial duplication model. We further illustrate the results by application to real data.

AB - 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 else where. 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,..., in large graphs, and apply our results to the partial duplication model. We further illustrate the results by application to real data.

UR - http://www.scopus.com/inward/record.url?scp=46349086834&partnerID=8YFLogxK

U2 - 10.1155/2008/190836

DO - 10.1155/2008/190836

M3 - Journal article

AN - SCOPUS:46349086834

VL - 2008

JO - Journal of Applied Mathematics

JF - Journal of Applied Mathematics

SN - 1110-757X

M1 - 190836

ER -

ID: 203905158