Computational Systems Biology Course | IIT Madras Prof. Karthik Raman
Course Details
| Exam Registration | 143 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Biological Sciences & Bioengineering, Computational Biology |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 26 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlocking the Secrets of Life: A Deep Dive into Computational Systems Biology
Every living cell is a marvel of engineering, a complex system where metabolic, signaling, and regulatory networks interact in a beautifully concerted dance. Understanding this intricate interplay is the key to advancing medicine, biotechnology, and our fundamental knowledge of life itself. This is where Computational Systems Biology comes in—a powerful discipline that applies mathematical modeling and computational tools to decode biological complexity.
We are excited to present a comprehensive 12-week course designed to equip you with the core principles and practical skills of this transformative field. Taught by a leading expert from one of India's premier institutions, this course offers a unique blend of theoretical knowledge and hands-on application.
Meet Your Instructor: Prof. Karthik Raman
This course is led by Prof. Karthik Raman, a Professor at the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras. Prof. Raman's research group is at the forefront of developing algorithms and computational tools to understand, predict, and manipulate complex biological networks.
His expertise spans:
- Microbiome Analysis
- In Silico Metabolic Engineering
- Biological Network Design & Analysis
Prof. Raman also coordinates the Centre for Integrative Biology and Systems mEdicine (IBSE) and is a core member of the Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI) at IIT Madras. An accomplished educator, he teaches computational and systems biology and is the author of the textbook "An Introduction to Computational Systems Biology."
Course Overview: What You Will Learn
This undergraduate/postgraduate level course provides a systematic, quantitative approach to studying biological systems. Over 12 weeks, you will move from foundational concepts to cutting-edge applications, gaining skills highly valued in both academia and industry.
Intended Audience: Students and professionals in Biological Sciences, Bioengineering, Computational Biology, or related fields with an interest in quantitative biology.
Prerequisites: Basic knowledge of a high-level programming language (preferably MATLAB) and a keen interest in biology.
Detailed 12-Week Course Layout
| Week | Topics Covered |
|---|---|
| Week 1 | Introduction to Mathematical Modelling |
| Week 2 | Introduction to Static Networks |
| Week 3 | Network Biology and Applications |
| Week 4 | Reconstruction of Biological Networks |
| Week 5 | Dynamic Modelling: ODEs & Parameter Estimation |
| Week 6 | Evolutionary Algorithms; Guest Lecture on Drug Development Modelling |
| Week 7 | Constraint-based Modelling of Metabolic Networks |
| Week 8 | Perturbations to Metabolic Networks |
| Week 9 | Elementary Modes & Applications of Constraint-based Modelling |
| Week 10 | Constraint-based Modelling Recap; 13C Metabolic Flux Analysis |
| Week 11 | Modelling Regulation, Host-Pathogen Interactions, System Robustness |
| Week 12 | Advanced Topics: Robustness, Evolvability, Intro to Synthetic Biology |
Hands-On Learning & Industry Relevance
A significant highlight of this course is its emphasis on practical, hands-on learning. You will work with various software tools and computational methods central to modern systems biology research. This practical experience is designed to make you industry-ready.
Industry Support: The skills taught in this course are directly applicable and supported by bioprocess industries and computational biology companies such as MedGenome and Vantage Research. Careers in metabolic engineering, drug discovery, and biotech data science await skilled computational systems biologists.
Essential Reading & Textbook
To complement the lectures, the following textbooks are recommended, including the instructor's own authoritative work on the subject:
- Raman K (2021) An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks. Chapman and Hall/CRC.
- Voit E (2012) A First Course in Systems Biology. Garland Science.
- Klipp E (2009) Systems Biology: A Textbook. Wiley-VCH.
- Newman MEJ (2011) Networks: An Introduction. Oxford Univ. Press.
Why Enroll in This Computational Systems Biology Course?
This course is more than just a series of lectures; it's a gateway to mastering a interdisciplinary science that is shaping the future of biology and medicine. You will learn to build models that can predict cellular behavior, design novel metabolic pathways for engineering, and understand the principles of robust biological design.
Under the guidance of Prof. Karthik Raman, you will gain insights from a researcher actively contributing to the field. Whether you aim to pursue research, enhance your professional skill set, or simply satisfy a deep curiosity about how life works at a systems level, this course offers the perfect foundation.
Embark on this 12-week journey to decode the logic of life through computation and mathematics. Enroll today and take the first step towards becoming a proficient computational systems biologist.
Enroll Now →