Srujan Shetty – Unlocking the Future of Biotechnology with Machine Learning Mastery

Srujan Shetty

Introduction

Highly skilled and motivated biotechnology professional with a strong background in Python, machine learning, and the development of predictive models. Experienced in web-based prediction systems and drug discovery applications, with expertise in molecular docking and dynamics.

Projects

• Developed a Predictive Model for HMG-CoA Reductase Bioactivity, achieving 86% accuracy with a Random Forest regression model.
• Web-Based Prediction of Protein-Ligand Docking Scores across multiple organs using Graph Neural Network models.
• Retrieved and filtered high-quality reads from colorectal cancer sequencing data, identifying key mutations and potential molecular markers.
• Conducted in-silico computational analysis of cancer exome datasets to identify molecular markers.

Education

• BE in Biotechnology from RV College of Engineering, CGPA: 8.11
• 12th Grade: 93.8%, 10th Grade: 89.2%

Technical Skills & Interests

• Python
• Machine Learning
• MS Office
• Development of Predictive Models
• Molecular Docking
• Molecular Dynamics

Extra Curricular Activities

• Maintenance Head in Team Krushi
• Participated in regional level Kabbadi
• Volunteering in NSS

Publications & Conferences

• Publication: “Understanding Insulin Mechanisms, Economic Implications, and Future Prospects”. DOI: Link
• Attended and presented research at international conference on “Artificial Intelligence and Machine Learning in Applied Biotechnology” at RVCE Bengaluru
• Attended and presented at Jnana Vijnana Tantrajnana Mela 2024 organized by Sri Adichunchanagiri Kshethra, Mandya

Internship

Research and Development Intern at COE in Computational Genomics, RVCE

Certificates

• Computer Aided Drug Design – NPTEL
• Bioengineering: Biology and Medicine – NPTEL
• Precision Medicine – COURSERA

“`

Cover Letter:

I am excited to apply for the Genome Analyst position at Medgenome. With a strong background in genomics, bioinformatics, and data analysis, I am eager to contribute my expertise to your team. My experience in analyzing complex genomic data and developing insights to support research and clinical applications aligns well with the goals of your organization.
I would welcome the opportunity to discuss how my experience aligns with your team’s objectives. Thank you for your time and consideration. I look forward to the possibility of contributing to Medgenome and would appreciate the chance to further explore this opportunity.
Sincerely,
Srujan Shetty