Institutions | About Us | Help | Gaeilge
rian logo

Go Back
Edge-weighting of gene expression graphs
Kerr, Gráinne; Perrin, Dimitri; Ruskin, Heather J.; Crane, Martin
In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes. These data, when subjected to clustering and classification procedures, can assist in identifying patterns and providing insight on biological processes. To understand the properties of complex gene expression datasets, graphical representations can be used. Intuitively, the data can be represented in terms of a bipartite graph, with weighted edges corresponding to gene-sample node couples in the dataset. Biologically meaningful subgraphs can be sought, but performance can be influenced both by the search algorithm, and, by the graph-weighting scheme and both merit rigorous investigation. In this paper, we focus on edge-weighting schemes for bipartite graphical representation of gene expression. Two novel methods are presented: the first is based on empirical evidence; the second on a geometric distribution. The schemes are compared for several real datasets, assessing efficiency of performance based on four essential properties: robustness to noise and missing values, discrimination, parameter influence on scheme efficiency and reusability. Recommendations and limitations are briefly discussed.
Keyword(s): Bioinformatics; Numerical analysis; Statistical physics; Computer simulation; edge-weighting; weighted graphs; gene expression; bi-clustering
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Kerr, Gráinne, Perrin, Dimitri, Ruskin, Heather J. ORCID: 0000-0001-7101-2242 <> and Crane, Martin ORCID: 0000-0001-7598-3126 <> (2009) Edge-weighting of gene expression graphs. Advances in Complex Systems, 13 (2). pp. 217-238. ISSN 0219-5259
Publisher(s): World Scientific Publishing
File Format(s): application/pdf
Related Link(s):,
First Indexed: 2010-05-25 05:05:04 Last Updated: 2019-02-09 06:54:53