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Biology, engineering, and computer science can be integrated to learn about computation and systems biology. This is done to understand the systematic analysis and modeling of complex biological phenomena.

To know more about this, you should check [course_title] to ensure that you are in good hands. You are guaranteed to learn fundamentals of complex biological systems without getting confused about how things are done to improve emerging research areas.


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
Lecture 1: Introduction to Computational and Systems Biology 01:06:00
Lecture 2: Local Alignment (BLAST) and Statistics 01:17:00
Lecture 3: Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM) 01:20:00
Lecture 4: Comparative Genomic Analysis of Gene Regulation 01:22:00
Lecture 5: Library Complexity and Short Read Alignment (Mapping) 01:20:00
Lecture 6: Genome Assembly 01:08:00
Leture 7: ChIP-seq Analysis; DNA-protein Interactions 01:21:00
Lecture 8: RNA-sequence Analysis: Expression, Isoforms 01:20:00
Lecture 9: Modeling and Discovery of Sequence Motifs 01:22:00
Lecture 10: Markov and Hidden Markov Models of Genomic and Protein Features 01:18:00
Lecture 11: RNA Secondary Structure – Biological Functions and Prediction 01:23:00
Module: 02
Leture 12: Introduction to Protein Structure; Structure Comparison and Classification 01:06:00
Lecture 13: Predicting Protein Structure 01:04:00
Lecture 14: Predicting Protein Interactions 01:11:00
Lecture 15: Gene Regulatory Networks 01:19:00
Lecture 16: Protein Interaction Networks 01:21:00
Lecture 17: Logic Modeling of Cell Signaling Networks 01:14:00
Lecture 18: Analysis of Chromatin Structure 01:20:00
Lecture 19: Discovering Quantitative Trait Loci (QTLs) 01:22:00
Lecture 20: Human Genetics, SNPs, and Genome Wide Associate Studies 01:18:00
Lecture 21: Synthetic Biology: From Parts to Modules to Therapeutic Systems 01:22:00
Lecture 22: Causality, Natural Computing, and Engineering Genomes 00:52:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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