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~S5

This document is currently not available here.

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.

Share

 
COinS