Biomarkers prediction for hepatocellular carcinoma using machine learning techniques /
Ola Salah Eldin Ayoub Sayed
Biomarkers prediction for hepatocellular carcinoma using machine learning techniques / تنبؤ العلامات البيولوجية لسرطان الكبد باستخدام تقنيات التعليم الآلي Ola Salah El Din Ayoub Sayed ; Supervised Yasser Mostafa Kadah , Nagwan. M. Abdelsamee - Cairo : Ola Salah Eldin Ayoub Sayed , 2016 - 56 P. : charts , facsimiles ; 30cm
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
Biomarker Gene selection Microarray
Biomarkers prediction for hepatocellular carcinoma using machine learning techniques / تنبؤ العلامات البيولوجية لسرطان الكبد باستخدام تقنيات التعليم الآلي Ola Salah El Din Ayoub Sayed ; Supervised Yasser Mostafa Kadah , Nagwan. M. Abdelsamee - Cairo : Ola Salah Eldin Ayoub Sayed , 2016 - 56 P. : charts , facsimiles ; 30cm
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
Biomarker Gene selection Microarray