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Type
ThesisAuthors
Bahabri, Rihab R.Advisors
Bajic, Vladimir B.
Committee members
Gao, Xin
Moshkov, Mikhail

Program
Computer ScienceDate
2013-06Embargo End Date
2014-06-11Permanent link to this record
http://hdl.handle.net/10754/293891
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Show full item recordAccess Restrictions
At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2014-06-11.Abstract
Activities of DNA are to a great extent controlled epigenetically through the internal struc- ture of chromatin. This structure is dynamic and is influenced by different modifications of histone proteins. Various combinations of epigenetic modification of histones pinpoint to different functional regions of the DNA determining the so-called chromatin states. How- ever, the characterization of chromatin states by the DNA sequence properties remains largely unknown. In this study we aim to explore whether DNA sequence patterns in the human genome can characterize different chromatin states. Using DNA sequence motifs we built binary classifiers for each chromatic state to eval- uate whether a given genomic sequence is a good candidate for belonging to a particular chromatin state. Of four classification algorithms (C4.5, Naive Bayes, Random Forest, and SVM) used for this purpose, the decision tree based classifiers (C4.5 and Random Forest) yielded best results among those we evaluated. Our results suggest that in general these models lack sufficient predictive power, although for four chromatin states (insulators, het- erochromatin, and two types of copy number variation) we found that presence of certain motifs in DNA sequences does imply an increased probability that such a sequence is one of these chromatin states.Citation
Bahabri, R. R. (2013). PREDICTION OF CHROMATIN STATES USING DNA SEQUENCE PROPERTIES. KAUST Research Repository. https://doi.org/10.25781/KAUST-WY88Bae974a485f413a2113503eed53cd6c53
10.25781/KAUST-WY88B