Area of Research Interest

I focus on the identification of novel cancer biomarkers through Gene Expression Analysis and Machine-Learning Techniques. My work aims to enhance early detection, diagnosis, and personalized treatment of cancer by discovering key gene signatures that distinguish between healthy and cancerous cells. 

Methods

• Differential Gene Expression: Analyzing large RNA-sequence datasets to identify significant changes in gene expression between cancerous and non-cancerous tissues

• Machine Learning: Utilizing AI algorithms to select and validate potential biomarkers, enhancing diagnostic accuracy and enabling targeted treatment

• Data-Driven Insights: Employing bioinformatics and statistical methods for robust and reproducible findings

Applications
The identified biomarkers aim to:

• Enable earlier and more accurate cancer diagnosis

• Facilitate targeted therapy development

• Enhance treatment personalization, reducing side effects and improving outcomes

Current Projects

• Identification of Cervical Cancer Biomarkers using Bioinformatics and Machine Learning approaches