A scientific paper written by a research team from RENCI and the National Center for Supercomputing Applications (NCSA) was named the best application paper at the recent IEEE International Conference on Bioinformatics and Bioengineering (BIBE 2007).
The paper, MotifNetwork: A Grid-enabled Workflow for High-throughput Domain Analysis of Biological Sequences, was one of more than 600 submitted on scientific applications and the only one to receive an award. Its authors are RENCI Research Scientist Jeffrey L. Tilson and Gloria Rendon, Mao-Feng Ger and Eric Jakobsson of NCSA at the University of Illinois.
MotifNetwork is an effort to build an integrated suite of grid-enabled workflows for high throughput domain analysis of protein sequences. Traditionally, bioinformatics research involves analysis of genes and gene products—most often, proteins represented as sequences of amino acids. The proteins are analyzed by comparing their amino acid sequences, however, proteins also contain subsequences that define their activity and mode of regulation. These subsequences are called domains and motifs. Analysis of domains and motifs, rather than of protein sequences, often is a more productive way to study aspects of gene function, and gene and organism evolution. The analysis is computationally intensive because the possible combinations of protein subsequences grows exponentially as the motifs and domains interact.
MotifNetwork is the first user-friendly environment to facilitate motif/domain analysis. The workflow orchestration and enactment is handled by Taverna, software tools used to make workflows and distributed computing technology easy to use. MotifNetwork uses the Generic Service Toolkit (GST) to allow the workflow to use grid services and perform grid-based computations. Its end products are data, organized as matrices, and visualizations suitable for quick analysis.