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
Print OCLC #
Link to Catalog Record
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.
Share My Thesis If you are the author of this work and would like to grant permission to make it openly accessible to all, please click the button above.