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Biomarkers prediction for hepatocellular carcinoma using machine learning techniques / Ola Salah El Din Ayoub Sayed ; Supervised Yasser Mostafa Kadah , Nagwan. M. Abdelsamee

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ola Salah Eldin Ayoub Sayed , 2016Description: 56 P. : charts , facsimiles ; 30cmOther title:
  • تنبؤ العلامات البيولوجية لسرطان الكبد باستخدام تقنيات التعليم الآلي [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: Microarray is an effective innovation can recover and study the sub-atomic science of tissues and the quality expression estimations of the entire genome and the estimation of microarrays in comprehension the organic procedures basic a particular ailment which has an awesome part in finding new critical qualities for malignancies in Hepatocellular Carcinoma (HCC). In this work we give a procedure to extract significant genes which have role to understand the identification and characterization of key gene that play a role in the HCC and HCV replication cycle by apply univariate method and multivariate methods. These significant genes can be viewed as cheerful biomarkers in high throughput microarrays of HCC such as provided from univariate method (SPRY1, TXNIP, DDIT4, STC2, COL1A1) and multivariate methods (EEF1A1, FTL, ACTB) and others gene have impact in distinctive kind of cancers. Finally although each method has different procedure it gives me the key genes which have role in HCC
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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.M.Sc.2016.Ol.B (Browse shelf(Opens below)) Not for loan 01010110070081000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2016.Ol.B (Browse shelf(Opens below)) 70081.CD Not for loan 01020110070081000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

Microarray is an effective innovation can recover and study the sub-atomic science of tissues and the quality expression estimations of the entire genome and the estimation of microarrays in comprehension the organic procedures basic a particular ailment which has an awesome part in finding new critical qualities for malignancies in Hepatocellular Carcinoma (HCC). In this work we give a procedure to extract significant genes which have role to understand the identification and characterization of key gene that play a role in the HCC and HCV replication cycle by apply univariate method and multivariate methods. These significant genes can be viewed as cheerful biomarkers in high throughput microarrays of HCC such as provided from univariate method (SPRY1, TXNIP, DDIT4, STC2, COL1A1) and multivariate methods (EEF1A1, FTL, ACTB) and others gene have impact in distinctive kind of cancers. Finally although each method has different procedure it gives me the key genes which have role in HCC

Issued also as CD

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