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The [course_title] course focuses on the computational approaches for solving problems in systems biology. Through a series of case studies, you will learn how an effective match between the statement of a biological problem and the selection of an appropriate algorithm or computational technique can lead to fundamental advances. Several discrete and numerical algorithms used in the simulation, feature extraction, and optimisation for molecular, network and systems models in biology will also be discussed in the course.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: MIT

Course Curriculum

Module 01
Introduction and Protein Modeling Questions 00:08:00
Models of Proteins 00:12:00
Discrete Conformational Search 00:10:00
Binding and Docking 00:10:00
Molecular Dynamics Simulation 00:10:00
Molecular Dynamics and Electrostatics 00:11:00
Continuum Electrostatic Modeling I 00:12:00
Continuum Electrostatic Modeling II 00:14:00
Electrostatic Optimization and Design 00:10:00
Electrostatics Modeling 1 00:10:00
Electrostatics Modeling 2 00:09:00
Statistical Mechanics 00:13:00
Statistical Mechanics (cont.) 00:12:00
Module 02
Formulating and Simulating Network Models in Biology 00:12:00
Formulating Models 00:10:00
Nonlinear Dynamics and Stability 00:15:00
Steady-State Problems 00:11:00
Parameter Fitting and Estimation 00:10:00
Parameter Estimation; Robustness, Fragility, Control 00:07:00
2-D and 3-D Light Microscopy; Image Reconstruction 00:08:00
Deconvolution 00:09:00
Deconvolution II 00:11:00
Blind Deconvolution 00:12:00
Optical Flow 00:11:00
High-Throughput Data and its Analysis 00:08:00
Inference and Statistics 00:09:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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