Masters Theses
Parallel EST clustering for gene sequencing
Abstract
"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.
Department(s)
Computer Science
Degree Name
M.S. in Computer Science
Publisher
University of Missouri--Rolla
Publication Date
Fall 2003
Pagination
ix, 91 pages
Rights
© 2003 Rameshreddy Mudhireddy, All rights reserved.
Document Type
Thesis - Citation
File Type
text
Language
English
Subject Headings
Computer algorithms
Data structures (Computer science)
Molecular biology -- Data processing
Thesis Number
T 8421
Print OCLC #
55209569
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.
http://merlin.lib.umsystem.edu/record=b5088299~S5Recommended Citation
Mudhireddy, Rameshreddy, "Parallel EST clustering for gene sequencing" (2003). Masters Theses. 2436.
https://scholarsmine.mst.edu/masters_theses/2436
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