*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Atlanta, GA | Posted: February 15, 2012
Jackie Nemeth
School of Electrical and Computer Engineering
404-894-2906
Summary Sentence:
ECE Assistant Professor Bo Hong received the Best Paper Award at the 2011 IEEE International Conference on Bioinformatics and Biomedicine, held November 12-15 in Atlanta.
Full Summary:
ECE Assistant Professor Bo Hong on receiving the Best Paper Award at the 2011 IEEE International Conference on Bioinformatics and Biomedicine, held November 12-15, 2011 in Atlanta.
photo of Bo HongBo Hong received the Best Paper Award at the 2011 IEEE International Conference on Bioinformatics and Biomedicine, held November 12-15 in Atlanta.
An assistant professor in the School of Electrical and Computer Engineering (ECE) at Georgia Tech, Dr. Hong was honored for his paper, "Improving Prediction Accuracy of Protein-DNA Docking with GPU Computing." He shares this award with two coauthors–Jiadong Wu, his Ph.D. student, and Jun-tao Guo, a colleague from the Department of Bioinformatics and Biomedicine at the University of North Carolina at Charlotte.
Protein-DNA docking represents one of the most challenging problems in structural bioinformatics. Knowledge of how proteins interact with DNA is critical for understanding many key biological processes and for structure-based drug design. This paper describes a high performance computing method that Dr. Hong and his team have developed to tackle the protein-DNA docking problem using a GPU cluster. This protein-DNA docking algorithm integrates Monte-Carlo simulation and a simulated annealing method and has achieved 10.4 TFLOPS of sustained performance using 128 GPU cards, which represents 4Ă— speed up over a traditional cluster with 1000 CPU cores. Such improved computation capability accelerates the conformational space sampling for the docking algorithm and increases the chance of finding near-native protein-DNA structures.
