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Nucleosome Positioning Events and Probability Model Created with Probability Theory Application in a Human DNA Sequence

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AbstractThe histone code hypothesis predicts that histone modifications control chromatin processes such as gene expression, but their consequences are not highly predictable. Accordingly, nucleosome positioning is suggested to be a code that dictates distinct epigenetic states. The aim of this work was to mathematically model nucleosome positioning as a first step toward testing the nucleosome code hypothesis. Nucleosome positioning was predicted with NXSensor software in a human DNA sequence. Probability theory was applied to model nucleosome positioning; positioning events and probabilities were modeled, and then probabilities were calculated. Nucleosome positioning events were proportional to nucleosome occupancy, but they were not proportional to positioning probabilities. Based on our results, we proposed a general nucleosome positioning model, and we searched for evidence of the model in the literature. The proposed model can be applied to test the association between events and experimental data of both positioning and gene expression and cell states events to validate or reject the nucleosome code hypothesis.
Springer Science and Business Media LLC
Title: Nucleosome Positioning Events and Probability Model Created with Probability Theory Application in a Human DNA Sequence
Description:
AbstractThe histone code hypothesis predicts that histone modifications control chromatin processes such as gene expression, but their consequences are not highly predictable.
Accordingly, nucleosome positioning is suggested to be a code that dictates distinct epigenetic states.
The aim of this work was to mathematically model nucleosome positioning as a first step toward testing the nucleosome code hypothesis.
Nucleosome positioning was predicted with NXSensor software in a human DNA sequence.
Probability theory was applied to model nucleosome positioning; positioning events and probabilities were modeled, and then probabilities were calculated.
Nucleosome positioning events were proportional to nucleosome occupancy, but they were not proportional to positioning probabilities.
Based on our results, we proposed a general nucleosome positioning model, and we searched for evidence of the model in the literature.
The proposed model can be applied to test the association between events and experimental data of both positioning and gene expression and cell states events to validate or reject the nucleosome code hypothesis.

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