Integrative Predictive Modeling of Metastasis in Melanoma Cancer Based on MicroRNA, mRNA, and DNA Methylation Data

Date

2021-09-01

Author

Kutlay, Aysegul
Aydın Son, Yeşim

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

187
views

0
downloads

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 regulatory impact of genetic biomarkers for monitoring metastatic molecular signatures of melanoma by investigating the consolidated effect of miRNA, mRNA, and DNA methylation.

URI

https://hdl.handle.net/11511/94453

Journal

FRONTIERS IN MOLECULAR BIOSCIENCES

DOI

https://doi.org/10.3389/fmolb.2021.637355

Collections

Graduate School of Informatics, Article

Suggestions

OpenMETU
Core

Improving the Computer-Aided Estimation of Ulcerative Colitis Severity According to Mayo Endoscopic Score by Using Regression-Based Deep Learning Polat, Gorkem; Kani, Haluk Tarik; Ergenc, Ilkay; Alahdab, Yesim Ozen; Temizel, Alptekin; Atug, Ozlen (2022-11-01) Background Assessment of endoscopic activity in ulcerative colitis (UC) is important for treatment decisions and monitoring disease progress. However, substantial inter- and intraobserver variability in grading impairs the assessment. Our aim was to develop a computer-aided diagnosis system using deep learning to reduce subjectivity and improve the reliability of the assessment. Methods The cohort comprises 11 276 images from 564 patients who underwent colonoscopy for UC. We propose a regression-based deep ...
Incorporation of personal Single Nucleotide Polymorphism (SNP) data into a national level electronic health record for disease risk assessment, Part 3: An evaluation of SNP Incorporated National Health Information System of Turkey for prostate cancer Beyan, Timur; Aydın Son, Yeşim (2014-08-01) ©Timur Beyan, Yeşim Aydin Son.Background: A personalized medicine approach provides opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, the tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electronic medical records (EMRs)/electronic health records (EHRs). Today, various centr...
Incorporation of personal Single Nucleotide Polymorphism (SNP) data into a national level electronic health record for disease risk assessment, part 2: The incorporation of SNP into the national health information system of Turkey Beyan, Timur; Aydın Son, Yeşim (2014-08-01) ©Timur Beyan, Yeşim Aydin Son.Background: A personalized medicine approach provides opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, the tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electronic medical record (EMR)s/electronic health record (EHR)s systems. Today, various...
Leveraging the Molecular Signatures of Cancer for Dynamic Network Modeling Tunçbağ , Nurcan; Ayar , Enes Sefa (Orta Doğu Teknik Üniversitesi Enformatik Enstitüsü; 2022-10) Molecular heterogeneity and resistance to the treatment are among the obstacles in developing treatment strategies in cancer. Therefore, transforming patient-specific molecular data into clinically interpretable knowledge is fundamental in personalized medicine. However, not all molecular alterations drive cancer. The distinction of drivers from latent drivers and passengers, their cooperativity and exclusivity, and the temporal order of accumulation of molecular alterations is a crucial yet daunting, unsol...
Differential immune activation following encapsulation of immunostimulatory CpG oligodeoxynucleotide in nanoliposomes. Erikçi, E; Gürsel, Mayda; Gürsel, I (2011-02-01) The immunogenicity of a vaccine formulation is closely related to the effective internalization by the innate immune cells that provide prolonged and simultaneous delivery of antigen and adjuvant to relevant antigen presenting cells. Endosome associated TLR9 recognizes microbial unmethylated CpG DNA. Clinical applications of TLR9 ligands are significantly hampered due to their pre-mature in vivo digestion and rapid clearance. Liposome encapsulation is a powerful tool to increase in vivo stability as well as...

Citation Formats

A. Kutlay and Y. Aydın Son, “Integrative Predictive Modeling of Metastasis in Melanoma Cancer Based on MicroRNA, mRNA, and DNA Methylation Data,” FRONTIERS IN MOLECULAR BIOSCIENCES, vol. 8, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/94453.