My research areas include cellular aging and related diseases, statistical genetics, genome-wide association studies, and mathematical modeling of cancer. I am also interested in the data science of NGS and TCGA gene expression data sets. My research concerns mainly the mathematical and statistical analysis of biological systems at molecular level. I am also interested in Chemical Reaction Network Theory and Numerical Methods and Cancer Dynamics.




For updated projects, you can follow me on ResearchGate.



  1. Guven, E. (2022). The Decision of the Optimal Rank of a Non-negative Matrix Factorization Model for Gene Expression Datasets Utilizing Unit Invariant Knee Method. bioRxiv.


  1. Gene Expression Characteristics of Tumor and Adjacent Non-Tumor Tissues of Pancreatic Ductal Adenocarcinoma (PDAC) In-Silico EMİNE GÜVEN , Yayın Yeri: Iranian Journal of Biotechnology , 2022, https://dx.doi.org/10.30498/IJB.2021.292558.3092

  2. Non-negative Matrix Factorization and Differential Expression Analyses Identify Hub Genes Linked to Progression and Prognosis of Glioblastoma Multiform SEVİNÇ AKÇAY,EMİNE GÜVEN,Muhammad Afzal,Imran Kazmi , Yayın Yeri:Gene , 2022, https://dx.doi.org/10.1016/j.gene.2022.146395

  3. Screening the Significant Hub Genes by Comparing Tumor Cells, Normoxic and Hypoxic Glioblastoma Stem-like Cell Lines Using Co-Expression Analysis in Glioblastoma, EMİNE GÜVEN,Muhammad Afzal,Imran Kazmi , Yayın Yeri:Genes , 2022, https://dx.doi.org/10.3390/genes13030518

  4. Polycystic Ovarian Syndrome: A Complex Disease with a Genetics Approach Himani Nautiyal,Syed Sarim Imam,Sultan Alshehri,Mohammed Ghoneim,Muhammad Afzal,Sami I. Alzarea,EMİNE GÜVEN,Fahad A. Al-Abbasi,Imran Kazmi , Yayın Yeri:Biomedicines , 2022, https://dx.doi.org/10.3390/biomedicines10030540

  5. Modeling the Cluster Size Distribution of Vascular Endothelial Growth Factor (VEGF) Receptors EMİNE GÜVEN,Michael Wester,Jeremy S. Edwards,Ádám Miklós Halász , Yayın Yeri:Bioinformatics and Biology Insights , 2022 https://dx.doi.org/10.1177/11779322221085078

  6. Hydrogen peroxide induced loss of heterozygosity correlates with replicative lifespan and mitotic asymmetry in Saccharomyces cerevisiae, EMİNE GÜVEN,Lindsay A. Parnell,Erin D. Jackson,Meighan C. Parker,Nilin Gupta,Jenny Rodrigues,Hong Qin , Yayın Yeri:PeerJ , 2021, https://dx.doi.org/10.7717/peerj.2671

  7. Fitmix: An R Package for Mixture Modeling of the Budding Yeast S. cerevisiae Replicative Lifespan (RLS) Distributions, EMİNE GÜVEN,Hong Qin , Yayın Yeri:Applied Sciences , 2021,alhttps://dx.doi.org/10.3390/app11136114

  8. Gene expression analysis of MCF7 cell lines of breast cancer treated with herbal extract of Cissampelos pareira revealed association with viral diseases EMİNE GÜVEN , Yayın Yeri:Gene Reports , 2021, https://dx.doi.org/10.1016/j.genrep.2021.101169

  9. IDENTIFICATION OF BIOLOGICAL PATHWAYS AND POTENTIAL BIOMARKERS IN PANCREATIC ADENOCARCINOMA USING BIOINFORMATICS ANALYSES, EMİNE GÜVEN , Yayın Yeri:Journal of Applied Biological Sciences , 2021

  10. A comparison between the performance of Weibull and Log-logistic Aging Models on Saccharomyces cerevisiae lifespan data, EMİNE GÜVEN , Yayın Yeri:Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi , 2020, https://dx.doi.org/10.35193/bseufbd.600693

  11. The Effect of Gaussian Noise on Maximum Likelihood Fitting of Gompertz and Weibull Mortality Models with Yeast Lifespan Data, EMİNE GÜVEN,SEVİNÇ AKÇAY,Hong Qin , Yayın Yeri:Experimental Aging Research , 2019, https://dx.doi.org/10.1080/0361073X.2019.1586105