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Algorithms and Computational Techniques in Biology - Edukite
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Algorithms and Computational Techniques in Biology ( 9 REVIEWS )
843 STUDENTS
The course focuses on the computational approaches for solving problems in systems biology. Through a series of case studies, you …
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1 YEAR LEVEL 2 - CERTIFICATE COURSE BADGE COURSE CERTIFICATE
28
NUMBER OF UNITS NUMBER OF QUIZZES
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4 HOURS, 34 MINUTES
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The Algorithms and Computational Techniques in Biology 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.
Assessment 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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Algorithms and Computational Techniques in Biology - Edukite
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
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Algorithms and Computational Techniques in Biology - Edukite
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
Assessment
Submit Your Assignment
00:00:00
Certi cation
00:00:00
COURSE REVIEWS
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