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Indian Institute of Technology Madras

Computational Systems Biology

Indian Institute of Technology Madras and NPTEL via Swayam


Every living cell is the result beautifully concerted interplay of metabolic, signalling and regulatory networks. Systems biology has heralded a systematic quantitative approach to study these complex networks, to understand, predict and manipulate biological systems. Systems biology has had a positive impact on metabolic engineering as well as the pharmaceutical industry. This course seeks to introduce key concepts of mathematical modelling, in the context of different types biological networks. The course will cover important concepts from network biology, modelling of dynamic systems and parameter estimation, as well as constraint-based metabolic modelling. Finally, we will also touch upon some of the cutting-edge topics in the field. The course has a significant hands-on component, emphasizing various software tools and computational methods for systems biology.INTENDED AUDIENCE : Interested learnersPREREQUISITES : Basic knowledge of a high-level programming language (preferably MATLAB)INDUSTRY SUPPORT : Bioprocess industries / Computational Biology Companies, e.g. MedGenome, Vantage Research


Week 1 : Introduction to Mathematical ModellingWeek 2 : Introduction to Static NetworksWeek 3 : Network Biology and ApplicationsWeek 4 : Reconstruction of Biological NetworksWeek 5 : Dynamic Modelling of Biological Systems: Introduction, Solving ODEs & Parameter EstimationWeek 6 : Evolutionary Algorithms, Guest Lectures on Modelling in Drug DevelopmentWeek 7 : Constraint-based approaches to Modelling Metabolic NetworksWeek 8 : Perturbations to Metabolic NetworksWeek 9 : Elementary Modes, Applications of Constraint-based ModellingWeek 10: Constraint-based Modelling Recap, 13C Metabolic Flux AnalysisWeek 11: Modelling Regulation, Host-pathogen interactions, Robustness of Biological SystemsWeek 12: Advanced topics: Robustness and Evolvability, Introduction to Synthetic Biology, Perspectives & Challenges

Taught by

Prof. Karthik Raman



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