Identification of character non-independence in phylogenetic data using data mining and neural network techniques
Keywords and Phrases
"Difficult problems force innovative approaches and attention to detail, and their pursuit often results in contributions beyond the initial scope. This thesis investigates the data mining process resulting from examining the hypothesis of character non-independence in phylogenetic analyses. Phylogenetics is the study of identifying and classifying evolutionary relationships of organisms and plays an important role in the organization of biological data at levels ranging from molecules to ecosystems. It forms the basis of many biological research questions; hence, highly accurate estimates of evolutionary history are fundamentally important to most biological applications"--Abstract, leaf iv.
M.S. in Computer Science
University of Missouri--Rolla
Journal article titles appearing in thesis/dissertation
- Identifying character non-independence in phylogenetic data using data mining techniques
- Self-organizing maps: identifying character non-independence in phylogenetic data
x, 72 leaves
© 2004 Venkat Ram Ghatti, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
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=b5407847~S5
Ghatti, Venkat Ram, "Identification of character non-independence in phylogenetic data using data mining and neural network techniques" (2004). Masters Theses. 3652.