ENES KORAY SEFEROĞLU
ENES KORAY SEFEROĞLU
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Molecular Biologist & Bioinformatics Developer
I am Enes Koray Seferoğlu (2001), a senior Molecular Biology and Genetics student specializing in Computational Drug Discovery. While traditional workflows often separate biology from analysis, I bridge this gap by independently engineering the algorithmic tools required to interpret complex R&D data.
My expertise lies in developing specialized bioinformatics engines, such as my hybrid saRNA/siRNA designer, which utilizes Nearest-Neighbor thermodynamics to modulate dual genetic targets. From predicting CRISPR efficiency to quantifying miRNA oncogenic risk, I focus on building high-performance, web-based solutions that accelerate the transition from biological theory to functional discovery. I am now seeking to leverage this hybrid skillset in a professional R&D environment to drive digital innovation in biotechnology.
RESEARCH & DEVELOPMENT PORTFOLIO :
RESEARCH & DEVELOPMENT PORTFOLIO :
Advanced Bioinformatics Tools
Tools developed to automate biological analysis using Python, AI, and Web Technologies.
Dual-Target RNA Designer: A hybrid saRNA/siRNA discovery engine that integrates Reynolds/Ui-Tei rational design rules with Nearest-Neighbor thermodynamic calculations (Δ G) to independently identify dual-function RNA candidates targeting two distinct genes simultaneously.
saRNA Designer & Generator: A thermodynamic optimization engine for designing Small Activating RNAs (saRNA) targeting promoter regions. Features Δ G calculation and Reynolds score implementation.
AI-Powered CRISPR-Cas9 Predictor: A Deep Learning (CNN) tool running client-side with TensorFlow.js to predict sgRNA on-target efficiency, trained on the Doench (2016) dataset.
TP53 3'-UTR miRNA Profiler: A precision oncology tool that detects patient-specific somatic mutations and analyzes their impact on miRNA binding sites in Anaplastic Thyroid Cancer.
Automated Malaria AI Diagnostician: A clinical decision support tool that utilizes CNN architectures and Grad-CAM technology to detect Plasmodium parasites with explainable deep learning.
Scientific Research & Algorithms
Academic studies and novel algorithms developed for molecular biology insights.
The miRES Scoring System (Novel Algorithm): Developed the "miRNA Risk Effect Score"—a proprietary multi-dimensional metric quantifying oncogenic potential by integrating Binding Energy, Functional Impact, Pathogenicity, and Evolutionary Conservation (PhyloP).
Microgravity Stress Response in Thyroid Cancer: Investigated the gene expression profiles (proliferation/apoptosis markers) of Thyroid Cancer cells under simulated microgravity conditions (TEXUS-53 & CELLBOX-2 Missions).
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