Category Archives: bioinformatics

Oct 2007 Dagstuhl Seminar Invitation

I have been invited to attend a Dagstuhl Seminar in May of 2008 on Graph Drawing with Applications to Bioinformatics and Social Sciences. This is a very timely event for me, as I am working with a number of grad students, namely Mike Bennett, Mike Farrugia and Eamon Phelan on just these two areas. In addition Brendan Sheehan MSc, one of my grad students, has been developing the research and method behind CellTransformer: A Tool to Generate Reaction Networks through Graph Transformation. The timing is a little tight as I need to fly to Australia shortly afterwards where I’m the Late Breaking Results Co-Chair for Pervasive 2008, the Sixth International Conference on Pervasive Computing.

I’m looking forward to hearing about work in both Bioinformatics and the Social Sciences and any new techniques and applications that are emerging.

To quote to organisers!

“Automated graph drawing deals with the layout of relational data arising from computer science (data base design, data mining, software engineering), and other sciences such as bioinformatics (metabolic networks, protein-protein interaction), business informatics (business process models), and criminalistics (social networks, phone-call graphs). In mathematical terms, such relational data are modeled as graphs or more general structures such as hypergraphs, clustered graphs, or compound graphs. Graph drawing communicates the relational information through diagrams drawn in the plane. The main objective is to display the data in a meaningful fashion, that is, in a way that shows well the underlying structures, and that often depends on the application domain.

In this seminar, we will to focus on graph drawing in two important application domains: bioinformatics (metabolic pathways, regulatory networks, protein-protein interaction) and social sciences and criminalistics (case information diagrams, phone-call graphs). In both application domains, the underlying information is usually stored in large data bases constituting a huge and complex graph, but only a suitable fraction of this graph is visualized and the exploration of the underlying graph is guided by the user. Thus, the user becomes a central actor that triggers dynamic updates of the displayed graph and its layout. The support of application-specific update functionality in conjunction with high quality graph layout is essential in order to gain user acceptance in the targeted application areas.”

Sept 2007 CellTransformer: A Tool to Generate Reaction Networks through Graph Transformation

Brendan Sheehan MSc, one of the PhD scholars I supervise is off to The Eighth International Conference on Systems Biology, Long Beach California Oct 1-6, 2007. He is attending various tutorials and presenting a poster on his research, namely: “CellTransformer: A Tool to Generate Reaction Networks through Graph Transformation

ICSB 2007

Abstract:
Rule-based models provide a declarative means to construct a computational model of biological systems. Rules specify how the model can evolve over time by transforming the underlying data or model into its next state. Most rule-based systems operate on strings. Graph transformation systems (GTS) can provide a more direct and intuitive description of many kinds of biological data such as protein-interaction data and data relating to cell-signalling pathways. Here we implement the GTS based formalism defined by Blinov et al to help generate molecular reactions based on rules that describe interactions between protein domains. We use the GTS tool AGG to implement the tool as a plugin for the forthcoming version of CellDesigner.
by Sheehan and Quigley.