Seminars & Events

Mathematics and Computer Science Division Seminar
"SEBINI (with CABIN) - an architecture to support systems biology through network inference"

DATE: April 16, 2007
TIME: 2:00pm
SPEAKER: Ronald Taylor, Pacific Northwest National Laboratory, Richland, WA
LOCATION: Bldg: 221, Conference Room A216, Argonne National Laboratory
HOST: Terry Disz

Description:
Inference of mRNA transcriptional regulatory networks, protein-protein interaction networks, and protein activation/inactivation-based signal transduction networks are critical tasks in systems biology. Experiments are now producing data in quantities large enough for researchers to attempt to reconstruct such networks. This talk will give a very brief introduction to the concept of network reconstruction, and then will describe the Software Environment for Biological Network Inference (SEBINI), a project at the US Dept of Energy's Pacific Northwest National Laboratory, which has recently been used to form the backbone of the exploratory analysis pipeline developed for the joint ORNL/PNNL DOE Genomes-to-Life project for finding protein-protein interaction networks in bacteria, based on bait-prey mass spec experiments. The SEBINI platform is also being used to infer networks in PNNL's EMSL Membrane Grand Challenge project. The underlying goal of SEBINI is to advance network inference and construction of network-centric databases via the deployment and improvement of state-of-the-art network reconstruction algorithms , making such methods available to the general community. This talk will also feature CABIN (Collective Analysis of Biological Interaction Networks) and its use for integrating evidence from multiple interaction networks obtained from public databases and inference methods.

The second half of the talk will consist of a live demonstration of SEBINI, via its web user interface and CABIN. A set of experiments will be uploaded for inference of a network that can be permanently stored, visualized (as a graph, on the web site) and passed on to other tools. In conclusion, there will be a brief discussion of SEBINI’s usefulness in (1) linking derived networks to other bioinformatics tools for network annotation, refinement, and dynamic modeling, (2) serving as a front end for employment of network inference algorithms on large-scale computing resources, and (3) serving as an analysis platform for development of connections between networks of different types, i.e., to do systems biology “in the large” and to support model-fitting across different levels in the cell. Thus, the authors hope that SEBINI and CABIN will be of interest not just to the proteomics-based user community at PNNL and ORNL, but to users who are interested in network building of any sort.

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