Research Overview | Mahir Yusuf Acan

Research Areas

My research focuses on the intersection of molecular biology, genetics, and bioinformatics, with applications in medicine and healthcare.

Publications (MLA Format)

Açan, Mahir Yusuf. “Clustering of P53 and CENPA Regulation in MCF10A Cells Using Gene Expression Profiles: Application of K-means Algorithm.” 20 Apr. 2023.
Eroltu, Kaan, and Mahir Yusuf Açan. “A Comparative Study of Machine Learning Algorithms for Parkinson’s Disease Diagnosis.” 3 Apr. 2023.
Açan, Mahir Yusuf, and Zafer Yüksel. “Investigation of MEF2A Activation and Its Relationship with Pathways.” 11 Mar. 2021.
Açan, Mahir Yusuf, and Zafer Yüksel. “Investigation of the Effect of the MEF2A Variant on Myocardial Infarction and Coronary Artery Disease.” 12 Nov. 2020.

Research Projects

1. Clustering of P53 and CENPA Regulation in MCF10A Cells

Published: April 20, 2023

Analysis of P53 and CENPA clustering and regulation in MCF10A cells using:

Gene expression profiles
K-means clustering algorithm
Bioinformatics analysis tools
Statistical modeling

This research applies machine learning techniques to understand gene regulation patterns in cancer cell models, specifically focusing on the interplay between tumor suppressor protein P53 and centromere protein CENPA.

Keywords: P53, CENPA, Gene Expression, K-means Clustering, Bioinformatics, MCF10A Cells, Cancer Research

2. Machine Learning for Parkinson’s Disease Diagnosis

Published: April 3, 2023
Co-author: Kaan Eroltu

A comparative study evaluating different machine learning algorithms for diagnosing Parkinson’s disease. This research demonstrates the potential of AI and machine learning in early detection and diagnosis of neurodegenerative diseases.

Keywords: Machine Learning, Parkinson’s Disease, Diagnosis, Healthcare AI, Comparative Analysis, Neurodegenerative Diseases

3. MEF2A Activation and Pathway Relationships

Published: March 11, 2021
Co-author: Zafer Yüksel

Investigation of MEF2A (Myocyte Enhancer Factor 2A) activation mechanisms and its relationships with various cellular pathways. This research explores how MEF2A functions in gene regulation and its implications for cardiovascular health.

Keywords: MEF2A, Gene Activation, Cellular Pathways, Signal Transduction, Cardiovascular Research

4. MEF2A Variant Effects on Cardiovascular Disease

Published: November 12, 2020
Co-author: Zafer Yüksel

Comprehensive investigation of the effect of the MEF2A genetic variant on myocardial infarction and coronary artery disease. This research explores genetic factors that influence cardiovascular health and disease progression, providing insights into personalized medicine approaches.

Keywords: Genetics, Cardiovascular Disease, MEF2A Gene, Myocardial Infarction, Coronary Artery Disease, Risk Factors, Genetic Variants

Research Interests

🧬 Molecular Biology & Genetics: Gene regulation, genetic markers, disease genetics
💻 Bioinformatics: Computational analysis of biological data, machine learning in genomics
🦷 Oral Health Research: Dental genetics, oral disease mechanisms (future specialization)
🏥 Precision Medicine: Data-driven approaches to personalized healthcare
📊 Statistical Genomics: Application of statistical methods to genomic data

Academic Profiles & Publications

📚 Google Scholar: View Publications
🔬 ORCID: 0000-0003-0540-7099
📖 ResearchGate: View Profile
🎓 Academia.edu: View Profile

Tools & Technologies

Programming & Analysis:

Python (pandas, numpy, scikit-learn, biopython)
R (bioinformatics packages)
Machine Learning algorithms
Statistical analysis

Bioinformatics Tools:

Gene expression analysis
Sequence alignment
Pathway analysis
Clustering algorithms

Data Science:

Data visualization
Statistical modeling
Predictive analytics

Future Research Directions

Oral Health & Dentistry

Planning to specialize in oral health research, combining clinical dentistry with computational biology and data science.

Healthcare Data Science

Continuing to develop innovative data-driven solutions for medical diagnostics and treatment planning.

Collaborative Research

Open to collaborations in:

Dental genetics research
Bioinformatics projects
Healthcare data analytics
Clinical research studies

Research Philosophy

“Combining traditional biological research with modern computational methods to unlock new insights in healthcare and medicine.”

Contact for Research Collaboration

📧 Email: mahiryusuf531@gmail.com
💼 LinkedIn: linkedin.com/in/mahiryusufacan
🔗 Portfolio: zaap.bio/mahiryusufacan

MAPK Kinases Signaling Pathways

Abstract This research provides a comprehensive analysis of mitogen-activated protein kinase (MAPK) signaling pathways, which play crucial roles in cellular processes including proliferation, differentiation, apoptosis, and stress responses. Introduction MAPK pathways are evolutionarily conserved signaling cascades that regulate fundamental cellular processes. Understanding these pathways is essential for comprehending normal cell function and disease mechanisms, particularly in cancer and inflammatory diseases. MAPK Pathway Overview Major MAPK Pathways ERK1/2 Pathway: Involved in cell proliferation and differentiation JNK Pathway: Stress response and apoptosis p38 MAPK Pathway: Inflammation and cell cycle regulation ERK5 Pathway: Cell survival and proliferation Research Focus Signal Transduction Mechanisms Detailed analysis of how MAPK pathways transmit signals from cell surface receptors to nuclear transcription factors. ...

MEF2A Gene's Impact on Coronary Artery Diseases

Abstract This research investigates the MEF2A (Myocyte Enhancer Factor 2A) gene and its significant role in the development and progression of coronary artery diseases (CAD). Understanding genetic factors that contribute to cardiovascular diseases is crucial for developing targeted prevention and treatment strategies. Introduction Coronary artery disease remains one of the leading causes of mortality worldwide. The MEF2A gene, a transcription factor involved in cardiac development and function, has been identified as a potential genetic marker for CAD susceptibility. ...

P53 and CENPA Clustering in MCF10A Cells Using K-means Algorithm

Abstract This research applies advanced bioinformatics and machine learning techniques to analyze the clustering and regulation of P53 and CENPA genes in MCF10A cells. Using gene expression profiles and the K-means clustering algorithm, we identify patterns of gene regulation and co-expression networks. Introduction P53 - The Guardian of the Genome The P53 tumor suppressor gene plays a critical role in: Cell cycle regulation DNA repair Apoptosis Genomic stability CENPA - Centromere Function CENPA (Centromere Protein A) is essential for: ...

A Comparative Study of Machine Learning Algorithms for Parkinson's Disease Diagnosis

Citation (MLA Format) Eroltu, Kaan, and Mahir Yusuf Açan. “A Comparative Study of Machine Learning Algorithms for Parkinson’s Disease Diagnosis.” 3 Apr. 2023. Abstract This research presents a comprehensive comparative study of various machine learning algorithms for the diagnosis of Parkinson’s disease. The study evaluates the performance, accuracy, and clinical applicability of different ML approaches in early detection and diagnosis of this neurodegenerative disorder. Research Overview Parkinson’s Disease Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by: ...

Investigation of MEF2A Activation and Its Relationship with Pathways

Citation (MLA Format) Açan, Mahir Yusuf, and Zafer Yüksel. “Investigation of MEF2A Activation and Its Relationship with Pathways.” 11 Mar. 2021. Abstract This research investigates the activation mechanisms of MEF2A (Myocyte Enhancer Factor 2A) and its relationships with various cellular pathways. MEF2A is a transcription factor that plays crucial roles in gene regulation, particularly in cardiovascular development and function. Research Overview MEF2A Transcription Factor MEF2A belongs to the MEF2 family of transcription factors that are essential for: ...

Research Areas#

Publications (MLA Format)#

Research Projects#

1. Clustering of P53 and CENPA Regulation in MCF10A Cells#

2. Machine Learning for Parkinson’s Disease Diagnosis#

3. MEF2A Activation and Pathway Relationships#

4. MEF2A Variant Effects on Cardiovascular Disease#

Research Interests#

Academic Profiles & Publications#

Tools & Technologies#

Future Research Directions#

Oral Health & Dentistry#

Healthcare Data Science#

Collaborative Research#

Research Philosophy#

Contact for Research Collaboration#