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

dc.contributor.author Ersöz, Nur Sebnem
dc.contributor.author Guzel, Yasin
dc.contributor.author Bakir-Güngör, Burcu
dc.date.accessioned 2025-09-25T10:37:24Z
dc.date.available 2025-09-25T10:37:24Z
dc.date.issued 2019
dc.description.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. en_US
dc.identifier.doi 10.1109/SIU.2019.8806542
dc.identifier.isbn 9781728119045
dc.identifier.issn 2165-0608
dc.identifier.scopus 2-s2.0-85071969260
dc.identifier.uri https://doi.org/10.1109/SIU.2019.8806542
dc.identifier.uri https://hdl.handle.net/20.500.12573/2959
dc.language.iso tr en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof -- 27th Signal Processing and Communications Applications Conference, SIU 2019 -- Sivas -- 151073 en_US
dc.relation.ispartofseries Signal Processing and Communications Applications Conference
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Active Subnetwork en_US
dc.subject Biomarkers en_US
dc.subject Functional Enrichment en_US
dc.subject Protein Protein Interaction Network en_US
dc.subject Topological Analysis en_US
dc.subject Biomarkers en_US
dc.subject Diagnosis en_US
dc.subject Diseases en_US
dc.subject Genes en_US
dc.subject Proteins en_US
dc.subject Topology en_US
dc.subject Bioinformatics Methods en_US
dc.subject Differentially Expressed Gene en_US
dc.subject Functional Enrichments en_US
dc.subject Papillary Thyroid Cancer en_US
dc.subject Papillary Thyroid Carcinomata en_US
dc.subject Protein-Protein Interaction Networks en_US
dc.subject Sub-Network en_US
dc.subject Topological Analysis en_US
dc.subject Signal Processing en_US
dc.title Papiller Tiroid Karsinom Oluşumunda Etkili Moleküler Mekanizmaların İn Siliko Yöntemlerle Tespit Edilmesi en_US
dc.title.alternative In-Silico Identification of Papillary Thyroid Carcinoma Molecular Mechanisms en_US
dc.type Conference Object en_US
dspace.entity.type Publication
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gdc.description.department Abdullah Gül University en_US
gdc.description.departmenttemp [Ersöz] Nur Sebnem, Yaşam Ve Doǧa Bilimleri Fakültesi Biyomühendislik, Kayseri, Turkey; [Guzel] Yasin, Bilgisayar Ve Öǧretim Teknolojileri Eǧitimi, Süleyman Demirel Üniversitesi, Isparta, Turkey; [Bakir-Güngör] Burcu, Mühendislik Fakültesi, Abdullah Gül Üniversitesi, Kayseri, Turkey en_US
gdc.description.endpage 4
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 1
gdc.description.woscitationindex Conference Proceedings Citation Index - Science
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gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
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gdc.virtual.author Güngör, Burcu
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