This Course Structure is Curated as per the NEP-2020 Guidelines
Course Overview
The M.Sc. Computational Biology program at Malla Reddy Vishwavidyapeeth, Hyderabad, is a postgraduate course designed to equip students with the knowledge and skills to analyze and interpret biological data using computational tools and techniques. This program focuses on integrating biology, computer science, and mathematics to solve complex biological problems, such as genome analysis, protein structure prediction, and drug discovery.
This program focuses on equipping students with theoretical knowledge and hands-on skills from the 1st semester itself, ensuring they are well-prepared for both academic and professional challenges. The curriculum covers essential topics such as bioinformatics, genomics, systems biology, machine learning, and statistical modeling. Students gain hands-on experience in programming, data analysis, and the use of computational tools to address biological questions. The program also emphasizes interdisciplinary collaboration, research, and the development of innovative solutions to challenges in computational biology.
Graduates of this program are prepared to work as Computational Biologists, Bioinformatics Analysts, Data Scientists, or Research Scientists in academia, pharmaceutical companies, biotechnology firms, and healthcare organizations. With plenty of job opportunities globally, this program offers an excellent pathway for those interested in shaping the future of biology and healthcare through computational approaches.

Course Details
Description: 2 Years Degree Program
No. of Credits: 80 minimum and as specified
- Eligibility
- Curriculum Structure
- Program Outcomes
- Career Enhancement
- Higher Studies
- Job Roles & Progression
The minimum eligibility is a B.Sc. degree in Life Sciences, Biotechnology, Computer Science, or equivalent with at least 50% aggregate marks from a recognized university.
Semester | Name of the Subject |
Semester 1 | Introduction to Computational Biology, Programming for Biologists, Statistics for Biological Data, Molecular Biology and Genomics, Practical: Bioinformatics Tools and Databases |
Semester 2 | Algorithms in Bioinformatics, Structural Bioinformatics, Systems Biology, Machine Learning for Biology, Practical: Genomic Data Analysis |
Semester 3 | Advanced Genomics and Proteomics, Drug Discovery and Design, Big Data in Biology, Ethical and Legal Issues in Computational Biology, Practical: Research Project in Computational Biology |
Semester 4 | Emerging Trends in Computational Biology, Industry Applications, Thesis/Project Work |
- Bioinformatics Expertise: Proficiency in using computational tools and algorithms to analyze biological data.
- Genomic and Proteomic Analysis: Skills in interpreting genomic and proteomic data for research and applications.
- Machine Learning in Biology: Knowledge of applying machine learning techniques to solve biological problems.
- Drug Discovery: Competence in using computational methods for drug design and discovery.
- Interdisciplinary Collaboration: Ability to work across biology, computer science, and mathematics to address complex challenges.
- Research and Innovation: Skills in conducting cutting-edge research and contributing to advancements in computational biology.
- Ethical and Legal Knowledge: Understanding of ethical, legal, and regulatory issues in computational biology.
- Certification in Bioinformatics: Advanced training in computational tools and techniques for biological data analysis.
- Genomic Data Analysis Certification: Specialization in analyzing and interpreting genomic datasets.
- Machine Learning for Biology Certification: Focus on applying AI and machine learning to biological problems.
- Drug Discovery Certification: Training in computational methods for drug design and development.
- Ethics in Computational Biology Certification: Knowledge of ethical and legal frameworks in bioinformatics and genomics.
- Ph.D. in Computational Biology: Research opportunities in advanced genomics, systems biology, and drug discovery.
- Postgraduate Diploma in Bioinformatics: Specialized focus on computational tools and biological data analysis.
- M.Sc. in Data Science: Advanced study in data analytics and machine learning applications.
- M.B.A. in Biotechnology Management: Training in managing biotech and healthcare organizations.
Duration | Roles and Responsibilities | Salary Range |
0-3 years | Bioinformatics Analyst, Computational Biologist, Research Associate | ₹5,00,000 – ₹7,50,000 per annum |
3-5 years | Senior Computational Biologist, Data Scientist, Genomics Specialist | ₹7,50,000 – ₹10,00,000 per annum |
5-10 years | Project Manager in Computational Biology, Director of Bioinformatics, Healthcare Technology Consultant | ₹10,00,000 – ₹15,00,000 per annum |
10+ years | Chief Computational Biologist, Global Bioinformatics Advisor, Director of Research and Development | ₹15,00,000+ per annum |

Fee Structure Per Academic Year
Tuition Fee | Miscellaneous Fee | Scholarship | ||
150000 ₹ | 10000 ₹ | Above 90% – 30000 ₹ | Between 80-90% – 15000 ₹ | Between 70-80% – 7500 ₹ |
