Developing algorithms to understand the role of microbiome and other omics in cancer disease mechanism and therapy

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Tezin Türü: Doktora

Tezin Yürütüldüğü Kurum: Acıbadem Mehmet Ali Aydınlar Üniversitesi, Sağlık Bilimleri Enstitüsü, Medikal Biyoteknoloji Ana Bilim Dalı, Türkiye

Tezin Onay Tarihi: 2024

Tezin Dili: İngilizce

Öğrenci: TAYYİP KARAMAN

Danışman: Osman Uğur Sezerman

Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu

Özet:

Number of omics studies significantly increased after development of sequencing technology. Data obtained from microbiome, transcriptome proteome, metabolome and other omics studies play a crucial role in understanding the disease mechanism and developing new diagnosis and treatment techniques. Each omics study provides very important outcomes, however combining multiple omics data can give even more detailed and specific result. There are so many parameters that directly or indirectly affect the disease mechanism of occurrence, especially complex diseases like cancer. This is the reason why multi-omics analysis is quite significant for evaluating those parameters to find the problem or to find a treatment methodology specifically. In this thesis, we obtained microbiome and transcriptome data from colorectal cancer patients. In addition to that, we made a pathway prediction analysis and then these three omics data (microbiome, transcriptome, and pathway abundance data) were performed integration analysis.