Dr. James Green
Systems and Computer Engineering
September 21, 2010
admission is free
Registration 18:00 - 18:30
Seminar 18:30 – 20:00 pm
University of Ottawa
The talk will begin by explaining how computational acceleration of scientific computing can lead to higher confidence protein identification in the context of tandem mass spectrometry (MS/MS). By bringing offline data analysis 'into the loop', we hope to control the instrument in real-time and achieve information-driven MS/MS. A key component of such a system involves exact string matching, where short query peptides must be searched against entire proteomes within strict real-time requirements. To this end, we have developed a number of exact string matching algorithms suitable for implementation on multicore architectures. Search throughput results are presented for the Cell B/E and NVDIA CUDA GPGPU platforms including performance comparisons with contemporary approaches. At present we are able to search the entire human proteome within less than 3ms using a commodity graphics card, satisfying the requirements for an information-driven MS/MS system.
James Green received his B.A.Sc. in Systems Design Engineering from the University of Waterloo in 1998. He then received his M.Sc.(Eng.) and PhD degrees from Queen's University in 2000 and 2005 respectively for research in the areas of computational genomics and proteomics. In 2000-2001, Dr. Green worked at Molecular Mining Corporation, a bioinformatics start-up company in Kingston Ontario, where he helped to develop novel analysis methods for the interpretation of gene expression data. In September 2005, Dr. Green joined the Department of Systems and Computer Engineering at Carleton University where he is now an Associate Professor. His research interests include pattern classification challenges in biomedical informatics. Current research projects include the prediction of protein structure and function, the design of novel assistive devices for the disabled, and the acceleration of computational mass spectrometry through implementation on novel computational platforms. His research is supported by grants from Carleton University, the Natural Sciences and Engineering Research Council, MITACS, the Ontario Research Fund, and the Canadian Foundation for Innovation.
In addition to research, Dr. Green puts considerable emphasis on teaching, and this has been recognized with two teaching awards. He currently enjoys teaching in the areas of Pattern Classification and Experiment Design, Microprocessor Systems, and Computer Architecture.
Outside of work, he enjoys running, curling, and swimming with his three sons.
Last modified 10-08-31