2026-09-20T09:59:49Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/918232026-06-06T00:49:00Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Manolis Kellis.
Giguzinsky, Orit
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-11-24T18:37:27Z
2014-11-24T18:37:27Z
2014
2014
http://hdl.handle.net/1721.1/91823
894225376
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 125-129).
Previous studies have shown that DNA methylation may 1 e associated with disease, aging, the rate of aging and genetics. In this thesis, age is accurately predicted from DNA methylation in brain and blood tissues using two different algorithms, Random Forest and Linear Regression. Relationships between DNA methylation, genetics, disease and aging rate were also identified. Furthermore, the differences between the real ages and the predicted ages were found to be associated with the age of onset of aging related disease. The findings presented in this thesis take us a step further in understanding the causes of aging and age related disease and further prove the theory that methylation is related to our internal biological clock and disease.
by Orit Giguzinsky.
M.Eng.
129 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Environmental and age effects on methylation changes in human brain and blood cells
Thesis
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<Abstract>Previous studies have shown that DNA methylation may 1 e associated with disease, aging, the rate of aging and genetics. In this thesis, age is accurately predicted from DNA methylation in brain and blood tissues using two different algorithms, Random Forest and Linear Regression. Relationships between DNA methylation, genetics, disease and aging rate were also identified. Furthermore, the differences between the real ages and the predicted ages were found to be associated with the age of onset of aging related disease. The findings presented in this thesis take us a step further in understanding the causes of aging and age related disease and further prove the theory that methylation is related to our internal biological clock and disease.</Abstract>
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