Motif-based centrality analysis of biological and other networks

Prof. Dr. Falk Schreiber (Institute for Computer Science Martin-Luther-University Halle-Wittenberg, Germany)

CSIRO ICT

DATE: 2008-05-22
TIME: 16:00:00 - 17:00:00
LOCATION: CSIT Seminar Room, N101
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ABSTRACT:
The increasing quality, size and complexity of biological networks in systems biology enforces the application and further development of network analysis methods for their investigation. Various approaches have been developed or employed from other fields of sciences to investigate these complex networks. The ranking of network elements, often called centrality analysis, is one of these methods. A centrality is a function which considers the network structure and assigns every vertex of the network a numeric value in a way that more important vertices (such as global regulators in a gene regulatory network or important web pages in the WWW) get higher centrality values.

Here we discuss and compare different centrality measures which can be used to analyse biological networks. Some of these centralities have been already studied in biological sciences; others are transferred, for example, from social network analysis. In particular we investigate gene regulatory networks to identify global regulators. However, this analysis shows that for good results biological knowledge has to be considered to improve the results of centrality analysis (in this case the identification of global regulators). This leads to a new complex class of centrality measures: motif-based centralities. This centrality is based on network motifs, small recurring sub-networks within a given network. Motif- based centrality yields interesting results for biological networks but can also be applied to other types of networks such as social and technical networks.

BIO:
My current research focuses on the representation, analysis, and visualisation of biological networks in their spatial and temporal embedding under consideration of related multimodal and multidimensional data. Goal of these research activities is to support the knowledge generation process in the life sciences. As coordinator of the Bioinformatics research of the IPK Gatersleben, one of the major plant research institutes in Germany, I am particularly interested in plant bioinformatics and plant systems biology.

http://bic-gh.ipk-gatersleben.de/~schreibe/