İnsanlarda Görülen Kanser Türleri̇ İçi̇n Teşhi̇s Ve Tedavi̇ Amaçli Si̇stem Bi̇yobeli̇rteçle...

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" İnsanlarda Görülen Kanser Türleri̇ İçi̇n Teşhi̇s Ve Tedavi̇ Amaçli Si̇stem Bi̇yobeli̇rteçleri̇ni̇n Di̇feransi̇yel Koekspresyon Yöntemi̇ İle Beli̇rlenmesi̇ "
Erdöl, Meltem Nur Arğa, Kazım Yalçın

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1109694
Doc. No	:	TLpq2476166397
Main Entry	:	Arğa, Kazım Yalçın
	:	Erdöl, Meltem Nur
Title & Author	:	İnsanlarda Görülen Kanser Türleri̇ İçi̇n Teşhi̇s Ve Tedavi̇ Amaçli Si̇stem Bi̇yobeli̇rteçleri̇ni̇n Di̇feransi̇yel Koekspresyon Yöntemi̇ İle Beli̇rlenmesi̇\ Erdöl, Meltem NurArğa, Kazım Yalçın
College	:	Marmara Universitesi (Turkey)
Date	:	2019
student score	:	2019
Degree	:	Master's
Page No	:	212
Abstract	:	Differential co-expression analysis, a new approach in systems biology, has emerged as a complementary method to traditional differential gene expression analysis. In order to understand the genetic background of diseases, it is important to reveal the interactions of genes in diseased and healthy conditions. In this study, several cancer types (gastric carcinoma, non-small cell lung carcinoma, pancreatic ductal adenocarcinoma) were examined using differential co-expression analyses and it was discussed how these results could be used for research of diagnostic and therapeutic applications in cancer. The relevant gene expression data were obtained from National Centre for Biotechnology Information (NCBI) database. In order to characterize the differentially co-expressed genes, the normalization of each data set and statistical analyses were performed. Co-expression profiles were constructed from gene clusters that differ in their expression in each type of cancer examined and genetic networks were established to indicate whether they were expressed differently in tumour and healthy individuals. Highly interacting sub-clusters of these networks were assigned as modules and these modules were investigated whether they are significant for diagnostic and therapeutic applications of cancer.
Subject	:	Bioengineering
	:	Genetics
	:	Systematic biology