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ALBUKHAITI HESHAM预答辩公告
浏览次数:日期:2019-05-07编辑:研究生教务办1

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论文题目

Using Different Approaches For Identification And Investigation Diseases Based On Genetic Data

答辩人

ALBUKHAITI HESHAM

指导教师

Professor: Luo Jiawei

答辩委员会

主席

ShuLin Wang

学科专业

Computer Science & Technology

学院

College of computer science and Electronic Engineering

答辩地点

318

答辩时间

2019/ 5/ 6

2:30 PM

学位论文简介

In this study, we studied diseases related to cancer with MicroRNA and Transcription Factors (TFs). We construct the Gene regulatory network to uncover the roles of MicroRNA and TFs in the cancer diseases of breast, throat and stomach cancer, as well as the classification of diseases based on medical data. In gastric genes we describe the complex interactions among genes with nonlinear property preserved and investigate genes playing important roles in the gastric cancer formation, we utilized the distance correlation as the measurement of the relevance to construct the gene co-expression networks in both gastric cancer and normal tissue datasets.

We constructed Gene Regulatory Network utilizing parallel expression datasets of miRNAs and mRNAs with MicroRNA and TFs. GRN uncovered some of the regulators that play significant roles in the regulation of cell proliferation and play important roles in cancer which are these regulators known to be associated with cancerous . GRN has shown many factors such as CREB1, E2F1 in BRCA and ARNT, AHR in THCA with the largest number of objectives. Also we carry out GO and pathway enrichment analyses with R package   for each targets of BRCA and THCA. In addition we developed classifier to select features and classify diseases based on biomedical data. We used hybrid method with k-means, ANOVA test and support vector machine.

主要学术成果

[1] Hisham Abdel Latif Al-Bukhari, Jiawei Luo, Using differential nonlinear gene co-expression network for identification gastric cancer-related genes. Biomedical Research, Vol. 28, No. 16, pp. 1-4, (2017). (SCI, Accepted and already published online via Allied Academies).

[2] Hisham Abdel Latif Al-Bukhari, Jiawei Luo, A hybrid approach to select features and classify diseases based on medical data, IOP Conference. Series: Materials Science and Engineering 322 062002,  pp. 062002 (2018). (EI Compendex, Accepted and already online).

[3] Hisham Abdel Latif Al-Bukhari, Jiawei Luo, A hybrid approach to select and Combine Gene Expression Regulation based on cancer datasets. Via Allied Academies,(2019) (SCI), Under Revision.


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