Masters Theses

Author

Luyang Wang

Keywords and Phrases

Drosophila melanogaster; Sleep; Sleep-wake transitions

Abstract

“Sleep is one of the most preserved and restorative behaviors of animals and is important in human health. Lack of sleep may cause numerous diseases. So the study of sleep rhythms is very essential and complicated. In order to simplify the process of studying sleep, the fruit fly Drosophila melanogaster, is utilized as a model organism for several reasons. Some of the molecular mechanisms that contribute to the circadian clock in the fruit fly were also found to generate similar cycles in mammals. In order to study sleep patterns in the fruit fly, experiments were designed and performed to observe the differences between genotypes and gender of flies. Sleep was also monitored under different environment conditions. Experiments last four days long, with sleep status recorded at each minute. Several variables can be derived from the original data for further statistical analysis. Ultimately it is of interest to characterize the sleep behavior of flies by identifying sleep-related variables based on the four days of sleep. We will investigate if these differ among fly types and genders. So cluster analysis and discriminant analysis has been applied to figure out the key features that would affect sleep cycle of flies. Also, an exponential model of current sleep duration based on past sleep and wake durations is fit to check differences of the parameter estimators between cluster groups”--Abstract, page iii.

Advisor(s)

Olbricht, Gayla R.

Committee Member(s)

Samaranayake, V. A.
Thimgan, Matthew S.

Department(s)

Mathematics and Statistics

Degree Name

M.S. in Mathematics and Statistics

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2014

Pagination

viii, 86 pages

Note about bibliography

Includes bibliographic references (page 85).

Rights

© 2014 Luyang Wang, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12060

Electronic OCLC #

1313117308

Included in

Biostatistics Commons

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