Graphlet-based measures are suitable for biological network comparison | Zendy

Wayne B. Hayes | Zendy; Kai Sun | Zendy; Nataša Pržulj | Zendy

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Graphlet-based measures are suitable for biological network comparison

Author(s) -

Wayne B. Hayes,

Kai Sun,

Nataša Pržulj

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts729

Subject(s) - enhanced data rates for gsm evolution , biological network , network topology , computer science , parametric statistics , network structure , stability (learning theory) , biological data , data mining , topology (electrical circuits) , mathematics , machine learning , artificial intelligence , statistics , biology , bioinformatics , combinatorics , operating system

Large amounts of biological network data exist for many species. Analogous to sequence comparison, network comparison aims to provide biological insight. Graphlet-based methods are proving to be useful in this respect. Recently some doubt has arisen concerning the applicability of graphlet-based measures to low edge density networks-in particular that the methods are 'unstable'-and further that no existing network model matches the structure found in real biological networks.

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