The analysis of gene deletions is a fundamental approach for investigating gene function. We applied machine learning techniques to predict phenotypic effects of gene deletions in yeast. We created a dataset containing features that potentially have predictive power and then used feature processing techniques to improve the dataset and identify features that are important for our classification problem. We evaluated four different classification algorithms, K-Nearest Neighbors, Support Vector Machine, Decision Tree, and Random Forest, with respect to this problem. We used our framework to complement the set of experimentally determined essential yeast genes produced by the Saccharomyces Genome Deletion Project and produce more than 2000 annotations for genes that might cause morphological alterations in yeast.
| Identifer | oai:union.ndltd.org:NCSU/oai:NCSU:etd-01032006-230402 |
| Date | 05 January 2006 |
| Creators | Saha, Soma |
| Contributors | Dr. Dennis Bahler, Dr. Xiaosong Ma, Dr. Steffen Heber |
| Publisher | NCSU |
| Source Sets | North Carolina State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://www.lib.ncsu.edu/theses/available/etd-01032006-230402/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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