Computational Models and Algorithms for Nucleosome Positioning
The dissertation research is focused on improving performance on genome wide nucleosome positioning. Nucleosome is the basic structural unit of DNA in eukaryotic cells. As nucleosomes limit the accessibility of the wrapped DNA to transcription factors and other DNA-binding proteins, their p...
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ndltd-fsu.edu-oai-fsu.digital.flvc.org-fsu_2529132020-06-18T03:09:11Z Computational Models and Algorithms for Nucleosome Positioning Zhang, Yu (authoraut) Liu, Xiuwen, 1966- (professor directing dissertation) Bass, Hank W. (university representative) Dennis, Jonathan H. (Jonathan Hancock) (committee member) Kumar, Piyush (committee member) Tyson, Gary Scott (committee member) Florida State University (degree granting institution) College of Arts and Sciences (degree granting college) Department of Computer Science (degree granting department) Text text Florida State University Florida State University English eng 1 online resource (98 pages) computer application/pdf The dissertation research is focused on improving performance on genome wide nucleosome positioning. Nucleosome is the basic structural unit of DNA in eukaryotic cells. As nucleosomes limit the accessibility of the wrapped DNA to transcription factors and other DNA-binding proteins, their positions play an essential role in regulations of gene activities. Experiments have indicated that DNA sequence strongly influences nucleosome positioning by enhancing or reducing their binding ability to nucleosomes, therefore providing an intrinsic cell regulatory mechanism. While some sequence features are known to be nucleosome forming or nucleosome inhibiting, however, existing models have limited accuracy in predicting quantitatively nucleosomes occupancy (i.e., statistical nucleosome positioning) based on DNA sequence. The study developed several algorithms to produce better features as well as more accuracy models to predict nucleosome positioning. It first proposed several models to classify a given DNA sequence as nucleosome forming sequence or nucleosome inhibiting sequence. Then, it turns the focus to predict the probability that a basepair is covered by any nucleosome. Moreover, based on a one basepair dataset, it found an intrinsic pattern which can be used to develop a single base pair nucleosome localization algorithm. Experimental results have shown the proposed methods are comparable or better than all existing solutions. A Dissertation submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Fall Semester, 2014. November 5, 2014. Includes bibliographical references. Xiuwen Liu, Professor Directing Dissertation; Hank W. Bass, University Representative; Jonathan H. Dennis, Committee Member; Piyush Kumar, Committee Member; Gary Tyson, Committee Member. Computer science FSU_migr_etd-9275 http://purl.flvc.org/fsu/fd/FSU_migr_etd-9275 This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. http://diginole.lib.fsu.edu/islandora/object/fsu%3A252913/datastream/TN/view/Computational%20Models%20and%20Algorithms%20for%20Nucleosome%20Positioning.jpg |
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The dissertation research is focused on improving performance on genome wide nucleosome positioning. Nucleosome is the basic structural unit of DNA in eukaryotic cells. As nucleosomes
limit the accessibility of the wrapped DNA to transcription factors and other DNA-binding proteins, their positions play an essential role in regulations of gene activities. Experiments have
indicated that DNA sequence strongly influences nucleosome positioning by enhancing or reducing their binding ability to nucleosomes, therefore providing an intrinsic cell regulatory
mechanism. While some sequence features are known to be nucleosome forming or nucleosome inhibiting, however, existing models have limited accuracy in predicting quantitatively nucleosomes
occupancy (i.e., statistical nucleosome positioning) based on DNA sequence. The study developed several algorithms to produce better features as well as more accuracy models to predict
nucleosome positioning. It first proposed several models to classify a given DNA sequence as nucleosome forming sequence or nucleosome inhibiting sequence. Then, it turns the focus to predict
the probability that a basepair is covered by any nucleosome. Moreover, based on a one basepair dataset, it found an intrinsic pattern which can be used to develop a single base pair
nucleosome localization algorithm. Experimental results have shown the proposed methods are comparable or better than all existing solutions. === A Dissertation submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Fall Semester, 2014. === November 5, 2014. === Includes bibliographical references. === Xiuwen Liu, Professor Directing Dissertation; Hank W. Bass, University Representative; Jonathan H. Dennis, Committee Member; Piyush Kumar, Committee
Member; Gary Tyson, Committee Member. |
author2 |
Zhang, Yu (authoraut) |
author_facet |
Zhang, Yu (authoraut) |
title |
Computational Models and Algorithms for Nucleosome Positioning |
title_short |
Computational Models and Algorithms for Nucleosome Positioning |
title_full |
Computational Models and Algorithms for Nucleosome Positioning |
title_fullStr |
Computational Models and Algorithms for Nucleosome Positioning |
title_full_unstemmed |
Computational Models and Algorithms for Nucleosome Positioning |
title_sort |
computational models and algorithms for nucleosome positioning |
publisher |
Florida State University |
url |
http://purl.flvc.org/fsu/fd/FSU_migr_etd-9275 |
_version_ |
1719321194480533504 |