Parallel EST clustering for gene sequencing
"Our work involves developing an intelligent, time- and memory-efficient parallel clustering algorithm for the soybean EST database (dbEST). Furthermore, we plan to analyze the resulting clusters for over- and under-clustering problems. The end result will be a tool for soybean researchers to help further the current research in gene identification."--Abstract, page iii.
M.S. in Computer Science
University of Missouri--Rolla
ix, 91 leaves
© 2003 Rameshreddy Mudhireddy, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Data structures (Computer science)
Molecular biology -- Data processing
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Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5088299~S5
Mudhireddy, Rameshreddy, "Parallel EST clustering for gene sequencing" (2003). Masters Theses. 2436.