Characterization of protein-interaction networks in tumors

Background: Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be formally represented as graphs, and approximating PINs as undirected graphs allows the network properties to be characterized using well-established graph measures. This paper outlines features of PINs derived from 29 studies on differential gene expression in cancer. For each study the number of differentially regulated genes was determined and used as a basis for PIN construction utilizing the Online Predicted Human Interaction Database. Results: Graph measures calculated for the largest subgraph of a PIN for a given differential-geneexpression data set comprised properties reflecting the size, distribution, biological relevance, density, modularity, and cycles. The values of a distinct set of graph measures, namely Closeness Centrality, Graph Diameter, Index of Aggregation, Assortative Mixing Coefficient, Con...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Alexander Platzer, Paul Perco, Arno Lukas, Bernd Mayer
• Keywords: BMCBI 2007, Graph Measures, Pins, Protein Lists