In recent years, the use of computational techniques such as modelling and machine learning has greatly contributed to the field of Biology, particularly Biotechnology, creating a new and emerging field of Computational Biology and Systems Biology. Various B. Tech and M. Tech programs have included these subjects in their course curricula, providing students with a valuable addition to their knowledge. However, as this is an emerging field, there are limited online courses and reading materials available. It is our hope that this course will provide a new dimension to its participants.Fundamentals of Computational Biology is a course designed to introduce students to the fundamentals of computational biology, including the basics of biotechnology, life sciences, mathematics, modelling, and computational approaches. This course is designed to be accessible to both undergraduate (B. Tech) and graduate (M. Tech) level students, and the goal is to provide them with a basic understanding of the computational and mathematical techniques in the field of biology, enabling them to apply them to the analysis of biological data.The course will feature online lectures and on-hand modelling/coding training, encouraging active participation from the students. For each lecture, course materials will be provided which will include in-depth topic-related notes, solved examples and codes for practice.The course includes weekly online assessments, allowing students' learning performance to be evaluated. Upon successful completion of the course, students will be awarded course completion certificates.
Overview
Syllabus
Week
Topics
Video Titles
Week-1
Course overview and basic concepts
Introduction to computational Biology
What are models?
Use of Mathematics in Biology
Week-2
Mathematical concepts in Biology
Concept of Vector algebra
Concept of Matrix algebra
Concept of Ordinary Differential Equations
Biological Models
Week-3
Basics of model building
Model building using ODE
Introduction to Bacterial growth kinetics
Different models of Bacterial growth kinetics
Introduction to Enzyme kinetics
Week-4
Application of models
Fundamentals of population dynamics
fundamentals of a graph theory
Basics of Data representation
Week-5
Data representation
Data representation using MATLAB T1 / Python
Data representation using MATLAB T2 / Python
Functions using MATLAB / Python
Week-6
Model simulations
Solving ODE equations using MATLAB T1 / Python
Solving ODE equations using MATLAB T2 / Python
Basics of Prey-predator model and population-based model building
Week-7
Modeling in healthcare and basic sciences
Infectious disease spread models, SIR, SI models
Introduction to Game theory, basic examples of game theories in biology
Modelling of game theories, prisoner’s dilemma, snow drift model
Week-8
Computational approach in Basic Physiology
Basics of circulatory system in humans
Basics of Respiratory system in humans
Modelling of respiration at cellular level
Week-9
Computational approach in Various Biological processes
Application of fluid mechanics principles in Biology
Basics of Transcription and Translation
Modelling of transcription and translation
Basics of Mutations and its importance
Week-10
Basics of Evolutionary processes
Mathematical models of Mutations
Basics of evolution and evolutionary processes
Mathematical models of evolutionary processes
Week-11
Applications of Computational approach in solving real world problems
Basics of Flux Balance Analysis
Computational approach to solve FBA
Molecular Switch and its application in the field of Biotechnology
Revision of Data representation
Week-12
Revision of model building and solving.
Revision of Basics of MATLAB / Python Programming
Revision of model building
Revision of examples of biological processes and modelling approach
Taught by
Dr. Tanushree Chatterjee and Dr. R.G. Brajesh
