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Proceedings Paper

Correlation-based biological networks
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Paper Abstract

We construct a correlation-based biological network from a data set containing temporal expressions of 517 fibroblast tissue genes at transcription level. Four relevant and meaningful connected subgraphs of the network, namely: minimal spanning tree, maximal spanning tree, combined graph of minimal and maximal trees, and planar maximally filtered graph are extracted and the subgraphs' geometrical and topological properties are explored by computing relevant statistical quantities at local and global level. The results show that the subgraphs are extracting relevant information from the data set by retaining high correlation coeffcients. The design principle of the underlying biological functions is reflected in the topology of the graphs.

Paper Details

Date Published: 5 January 2008
PDF: 11 pages
Proc. SPIE 6802, Complex Systems II, 680212 (5 January 2008); doi: 10.1117/12.759252
Show Author Affiliations
Won-Min Song, The Australian National Univ. (Australia)
Tomaso Aste, The Australian National Univ. (Australia)
T. Di Matteo, The Australian National Univ. (Australia)

Published in SPIE Proceedings Vol. 6802:
Complex Systems II
Derek Abbott; Tomaso Aste; Murray Batchelor; Robert Dewar; Tiziana Di Matteo; Tony Guttmann, Editor(s)

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