Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Integrative Omics Strategies for Rare Gynecological Diseases
Date
2022-09-18
Author
Özcan Kabasakal, Süreyya
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
156
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/100362
Conference Name
GYNOCARE COST Action Training School
Collections
Department of Chemistry, Conference / Seminar
Suggestions
OpenMETU
Core
INTEGRATIVE NETWORK MODELLING OF DRUG RESPONSES IN CANCER FOR REVEALING MECHANISM OF ACTION
Ünsal Beyge, Şeyma; Tunçbağ, Nurcan; Department of Medical Informatics (2021-9-6)
Classification of cancer drugs is crucial for drug repurposing since the cost and innovation deficit make new drug development processes challenging. Heterogeneity of cancer causes drug classification purely based on known mechanism of action (MoA) and the list of target proteins to be insufficient. Multi-omic data integration is necessary for a systems biology perspective to understand molecular mechanisms and interactions between cellular entities underlying the disease. This study integrates drug-target ...
Integrative Modeling of the Tumor Specific Structural Networks in Human Cancers
Tunçbağ, Nurcan (2017-05-15)
Integrative Predictive Modeling of Metastasis in Melanoma Cancer Based on MicroRNA, mRNA, and DNA Methylation Data
Kutlay, Aysegul; Aydın Son, Yeşim (2021-09-01)
Introduction: Despite the significant progress in understanding cancer biology, the deduction of metastasis is still a challenge in the clinic. Transcriptional regulation is one of the critical mechanisms underlying cancer development. Even though mRNA, microRNA, and DNA methylation mechanisms have a crucial impact on the metastatic outcome, there are no comprehensive data mining models that combine all transcriptional regulation aspects for metastasis prediction. This study focused on identifying the regul...
Integrative network modelling of the dasatinib treatment in glioblastoma stem cells
Senger, Gökçe; Tunçbağ, Nurcan; Department of Bioinformatics (2019)
Glioblastoma (GBM), the most aggressive type of the glial tumours, is thought to be widely promoted by stem-like cells. Although certain cancer types have been radically treated with Receptor Tyrosine Kinases (RTKs) inhibitors, prior studies demonstrate that treatment Glioblastoma Stem Cells (GSCs) with RTK inhibitors led to dynamic interconversion from proliferative to slow-cycling, persistent state. In this work, we use the publicly available RNA-Seq and ChIP-Seq data in naive patient-derived GBM cell lin...
Integromic Analysis of Genetic Variation and Gene Expression Identifies Networks for Cardiovascular Disease Phenotypes
Yao, Chen; Chen, Brian H.; Joehanes, Roby; Otlu, Burcak; Zhang, Xiaoling; Liu, Chunyu; Huan, Tianxiao; Tastan, Oznur; Cupples, L. Adrienne; Meigs, James B.; Fox, Caroline S.; Freedman, Jane E.; Courchesne, Paul; O'Donnell, Christopher J.; Munson, Peter J.; Keles, Sunduz; Levy, Daniel (Ovid Technologies (Wolters Kluwer Health), 2015-02-10)
Background-Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies have reported numerous single nucleotide polymorphisms (SNPs) to be associated with CVD, the role of most of these variants in disease processes remains unknown.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Özcan Kabasakal, “Integrative Omics Strategies for Rare Gynecological Diseases,” presented at the GYNOCARE COST Action Training School, Skopje, Makedonya, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100362.