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Gene-gene interaction detection and disease progression models for alzheimer disease / Fayroz Farouk Ibrahim Sherif ; Supervised Abdalla Sayed Ahmed , Yasser Mostafa Kadah , Manal Abdelwahed

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Fayroz Farouk Ibrahim Sherif , 2017Description: 100 P. : charts ; 30cmOther title:
  • الكشف عن التفاعلات الجينية و نماذج التطور لمرض الزهايمر [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: The discovery of genetic variants between two groups of healthy and diseased people contributes to the identification of genetic markers of Alzheimer's. We aim to find a new set of genetic changes strongly associated with Alzheimer's disease, and detecting the interactions between these variables (Epistasis interactions) using a new hybrid method combining statistical and biological methods based on (IHOEB). In addition, we have proposed a probability model through which early progression rates can be estimated and information on the level of disease severity and the time it takes to move to the next level can be expected
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2017.Fa.G (Browse shelf(Opens below)) Not for loan 01010110074054000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2017.Fa.G (Browse shelf(Opens below)) 74054.CD Not for loan 01020110074054000

Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

The discovery of genetic variants between two groups of healthy and diseased people contributes to the identification of genetic markers of Alzheimer's. We aim to find a new set of genetic changes strongly associated with Alzheimer's disease, and detecting the interactions between these variables (Epistasis interactions) using a new hybrid method combining statistical and biological methods based on (IHOEB). In addition, we have proposed a probability model through which early progression rates can be estimated and information on the level of disease severity and the time it takes to move to the next level can be expected

Issued also as CD

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