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. See More: https://bit.ly/2XhfMbH

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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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FREE
1 YEAR
LEVEL 2 - CERTIFICATE
COURSE BADGE
COURSE CERTIFICATE
28NUMBER OF UNITS
0NUMBER OF QUIZZES
4 HOURS, 34 MINUTES
HOME CURRICULUM REVIEWS
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.
Certification
Edukite courses are free to study. To successfully complete a course you must submit all the
assignment of the course as part of assessment. Upon successful completion of a course, you can
choose to make your achievement formal by obtaining your Certi cate at a cost of £49.
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Course Credit: MIT
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
COURSE CURRICULUM

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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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