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| LEADER |
00000cam a2200000Ka 4500 |
| 001 |
in00002784763 |
| 005 |
20150922151007.0 |
| 006 |
m fo d |
| 007 |
cr unu|||||||| |
| 008 |
121127s2012 txu obm 000 0 eng d |
| 035 |
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|a (OCoLC)ocn819417071
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| 035 |
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|a (TxCM)http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-10815
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| 040 |
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|a TXA
|c TXA
|d UtOrBLW
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| 049 |
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|a TXAM
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| 099 |
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|a 2012
|a Thesis
|a 1969.1/ETD-TAMU-2012-08-10815
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| 100 |
1 |
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|a Agyepong, Kwadwo.
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| 245 |
1 |
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|a Comparative performance analysis of the algorithms for detecting periodically expressed genes /
|c by Kwadwo Agyepong.
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| 264 |
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1 |
|a [College Station, Tex.] :
|b [Texas A&M University],
|c [2012]
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| 300 |
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|a 1 online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 500 |
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|a "Major Subject: Electrical Engineering"
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| 588 |
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|a Description from author supplied metadata (automated record created 2012-10-22 13:24:58).
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| 502 |
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|b Master of Science
|c Texas A&M University
|d 2012
|o http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-10815
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| 504 |
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|a Includes bibliographical references.
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| 516 |
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|a Text (Thesis)
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| 520 |
3 |
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|a Thus far, a plethora of analysis on genome-wide gene expression microarray experiments on the cell cycle have been reported. Time series data from these experiments include gene expression profiles that might be periodically expressed. However, the numbers and actual genes that are periodically expressed have not been reported with consistency, analysis on similar experiments reports disparate numbers of genes that are periodically expressed with scant overlap. This work ultimately compares the performance of five spectral estimation schemes in their ability to recover periodically expressed genes profiles. Lomb-Scargle (LS), Capon, Missing-Data Amplitude and Phase Estimation (MAPES), Real Value Iterative Adaptive Approach (RIAA) and Lomb-Scargle Periodogram Regression (LSPR) are rigorously studied and pitted against each other in various simulated testing conditions. Results obtained using synthetic and microarray data reveals that RIAA is an efficient and robust method for the detection of periodically expressed genes in short time series data that might be characterized with noisy and irregularly sampled data points.
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| 500 |
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|a Electronic resource.
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| 650 |
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4 |
|a Major Electrical Engineering.
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| 653 |
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|a MAPES
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| 653 |
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|a Time Series
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| 653 |
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|a Cell Cycle
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| 653 |
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|a Microarray
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| 653 |
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|a LSPR
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| 653 |
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|a RIAA
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| 653 |
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|a Capon
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| 653 |
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|a Lomb-Scargle
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| 700 |
1 |
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|a Dougherty, Edward R.,
|e thesis advisor.
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| 700 |
1 |
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|a Serpedin, Erchin,
|e thesis advisor.
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| 856 |
4 |
0 |
|u http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-10815
|z Link to OAK Trust copy
|t 0
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| 948 |
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|a cataloged
|b h
|c 2012/11/27
|d c
|e ceaton
|f 12:03:30 pm
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| 994 |
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|a C0
|b TXA
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| 999 |
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|a MARS
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| 999 |
f |
f |
|s f67f9621-395a-3211-9317-ecd9e94d8a24
|i a5e4ca23-eeb1-3558-a852-d194603600d0
|t 0
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| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|d Available Online
|t 0
|e 2012 Thesis 1969.1/ETD-TAMU-2012-08-10815
|h Other scheme
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| 998 |
f |
f |
|a 2012 Thesis 1969.1/ETD-TAMU-2012-08-10815
|t 0
|l Available Online
|