2026-09-19T06:31:48Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/532782022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
David K. Gifford.
Jammalamadaka, Arvind K. (Arvind Kumar), 1981-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2010-03-25T15:24:55Z
2010-03-25T15:24:55Z
2009
2009
http://hdl.handle.net/1721.1/53278
547364390
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 199-203).
Experiments in a variety of fields generate data in the form of a time-series. Such time-series profiles, collected sometimes for tens of thousands of experiments, are a challenge to analyze and explore. In this work, motivated by gene expression data, we provide several methods and models for such analysis. The methods developed include new clustering techniques based on nonparametric Bayesian procedures, and a confirmatory methodology to validate that the clusters produced by any of these methods have statistically different mean paths.
by Arvind K. Jammalamadaka.
Ph.D.
203 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Some methods and models for analyzing time-series gene expression data
Thesis
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Publication
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unknown
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