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Computer science has made incredible strides in past decade. Some
science areas such as biology and bioinformatics could benefit greatly
by exploiting these advances. However, it requires in-depth knowledge
from multiple computer science subfields to fully utilize the
computational power or storage resources offered by new technologies
in computer hardware, architecture, and system software. The more and
more complex computer systems have made performance tuning an
overwhelming task for computer scientists, not to mention for domain
scientists such as biologist or bio-chemists. As a result, most
bioinformatics applications currently used on daily basis by
scientists fail to take advantage of state-of-the-art computer
systems. In this project, we propose to focus on one important type
of bioinformatics research tools and investigate high-throughput
biological sequence search. We will conduct a comprehensive study of
performance optimization of popular biological sequence search
programs, and develop a set of techniques that can work in different
execution environments to automatically and transparently enhance the
programs' overall performance. More specifically, we propose to
develop the following key techniques:
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Faculty Collaborators
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