Papiller Tiroid Karsinom Oluşumunda Etkili Moleküler Mekanizmaların İn Siliko Yöntemlerle Tespit Edilmesi

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Abstract

Representing approximately 70% to 80% of thyroid cancers, papillary thyroid cancer (PTC) is the most common type of thyroid cancers. PTC is seen in all age groups, but it is seen more frequently in women than in men. Detection of biomarker proteins of papillary thyroid cancinoma plays an important role in the diagnosis of the disease. In this study, we aim to find target genes and pathways that are associated with papillar thyroid carcinoma, by integrating different bioinformatics methods. For this purpose, usingin-silico methodologies, candidate genes and pathways that could explain disease development mechanisms are identified. Throughout this study, firstly we identified differentially expressed genes as the amount of their protein product differ between patient and healthy groups. Secondly, by using active subnetworks search algorithms, topologic analyses and functional enrichment tests, candidate proteins,which could be thought as PTC biomarkers, and affected pathways are identified. © 2020 Elsevier B.V., All rights reserved.

Description

Keywords

Active Subnetwork, Biomarkers, Functional Enrichment, Protein Protein Interaction Network, Topological Analysis, Biomarkers, Diagnosis, Diseases, Genes, Proteins, Topology, Bioinformatics Methods, Differentially Expressed Gene, Functional Enrichments, Papillary Thyroid Cancer, Papillary Thyroid Carcinomata, Protein-Protein Interaction Networks, Sub-Network, Topological Analysis, Signal Processing

Fields of Science

03 medical and health sciences, 0302 clinical medicine

Citation

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Issue

Start Page

1

End Page

4