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This course introduces the basic computational methods used to understand the cell on a molecular level. It covers subjects such as the sequence alignment algorithms dynamic programming, hashing, suffix trees, and Gibbs sampling. Furthermore, it also focuses on computational approaches to genetic and physical mapping, genome sequencing, assembly, and annotation, RNA expression and secondary structure, protein structure and folding, and molecular interactions and dynamics.


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

Enumerative Solutions: Partial Digest Problem and Median Strings
Motifs and Median Strings 00:15:00
Dynamic Programming: Sequence Alignments
Global Alignment 00:15:00
Local Alignment 00:10:00
Spliced Alignment 00:05:00
More Efficient Alignment 00:10:00
Graph Theory: Sequencing Genes and Proteins
Peptide Graphs 00:10:00
Pattern Matching: Exact Matches, Gapless Alignments, and BLAST
Exact Pattern Matching 00:10:00
Suffix Trees 00:05:00
Suffix Arrays and BWTs 00:15:00
BLAST 00:10:00
Clustering: Microarrays and Phylogeny
Trees 00:15:00
Probabilistic Models and Machine Learning: Gene Annotation and Evolution
Hidden Markov Models I 00:05:00
Hidden Markov Models II 00:05:00
Gibbs Sampling 00:05:00
Random Projections 00:10:00
Another Probabilistic Method to Phase Haplotype Data 00:35:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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