M.Sc. Bioinformatics

Course Overview
The M.Sc. in Bioinformatics programme offers an interdisciplinary foundation in molecular biology, computational analysis, statistics and data analytics. This programme prepares students to handle complex biological data using computational modeling and AI tools, focusing on genomics, proteomics, personalized medicine, and synthetic biology. Graduates develop advanced skills in machine learning, drug discovery, metagenomics, systems biology, and multi-omics integration. The programme encourages research-oriented thinking, innovation, entrepreneurship, and leadership through applied projects and industry collaboration. Students gain hands-on experience with cutting-edge bioinformatics tools, software, and laboratory technologies, equipping them to contribute effectively to academia, healthcare, and industry.

Eligibility
Candidates who have completed a Bachelor’s degree in Science from a recognised University with an aggregate of 50% marks (45% for SC/ ST candidates) are eligible. The candidate should have studied Biology / Mathematics / Physics / Chemistry / Computer Science as one of the core courses.

Programme Title: M.Sc. Bioinformatics

Semester I

  • Fundamentals of Bioinformatics
  • Cell Biology
  • Programming for Bioinformatics: Python and Unix/Linux
  • Biochemistry and Molecular Genetics
  • Mathematics for Bioinformatics
  • Bioinformatics Tools and Database Lab 1
  • Fundamental Techniques in Life Sciences

Semester II

  • Algorithms in Bioinformatics and Computational Biology
  • Genomics and Transcriptomics
  • Structural Bioinformatics and Drug Design
  • Database Management and Web Technologies
  • Introduction to Machine Learning
  • Bioinformatics Tools and Database Lab 2
  • Structural Bioinformatics Lab

Semester III

  • Biostatistics and R
  • Proteomics and Systems Biology
  • Next-Generation Sequencing and Analysis
  • High Performance Cloud Computing
  • Immunology and Immunoinformatics
  • Metagenomics and Microbiome Analysis
  • High-throughput Data Analysis and R Lab
  • Immunoinformatics Lab
  • Metagenomics Analysis Lab

Semester IV

  • Research Methodology
  • Master's Thesis/Dissertation