About this Course

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Learner Career Outcomes

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started a new career after completing these courses

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got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
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Flexible deadlines
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Approx. 12 hours to complete
English

Skills you will gain

Bioinformatics AlgorithmsAlgorithmsPython ProgrammingAlgorithms On Strings

Learner Career Outcomes

43%

started a new career after completing these courses

33%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 12 hours to complete
English

Offered by

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Johns Hopkins University

Syllabus - What you will learn from this course

Content RatingThumbs Up97%(3,265 ratings)Info
Week
1

Week 1

4 hours to complete

DNA sequencing, strings and matching

4 hours to complete
19 videos (Total 112 min), 7 readings, 2 quizzes
19 videos
Lecture: Why study this?4m
Lecture: DNA sequencing past and present3m
Lecture: Genomes as strings, reads as substrings5m
Lecture: String definitions and Python examples3m
Practical: String basics 7m
Practical: Manipulating DNA strings 7m
Practical: Downloading and parsing a genome 6m
Lecture: How DNA gets copied3m
Optional lecture: How second-generation sequencers work 7m
Optional lecture: Sequencing errors and base qualities 6m
Lecture: Sequencing reads in FASTQ format4m
Practical: Working with sequencing reads 11m
Practical: Analyzing reads by position 6m
Lecture: Sequencers give pieces to genomic puzzles5m
Lecture: Read alignment and why it's hard3m
Lecture: Naive exact matching10m
Practical: Matching artificial reads 6m
Practical: Matching real reads 7m
7 readings
Welcome to Algorithms for DNA Sequencing10m
Pre Course Survey10m
Syllabus10m
Setting up Python (and Jupyter)10m
Getting slides and notebooks10m
Using data files with Python programs10m
Programming Homework 1 Instructions (Read First)10m
2 practice exercises
Module 130m
Programming Homework 130m
Week
2

Week 2

3 hours to complete

Preprocessing, indexing and approximate matching

3 hours to complete
15 videos (Total 114 min), 1 reading, 2 quizzes
15 videos
Lecture: Boyer-Moore basics8m
Lecture: Boyer-Moore: putting it all together6m
Lecture: Diversion: Repetitive elements5m
Practical: Implementing Boyer-Moore 10m
Lecture: Preprocessing7m
Lecture: Indexing and the k-mer index10m
Lecture: Ordered structures for indexing8m
Lecture: Hash tables for indexing7m
Practical: Implementing a k-mer index 7m
Lecture: Variations on k-mer indexes9m
Lecture: Genome indexes used in research9m
Lecture: Approximate matching, Hamming and edit distance6m
Lecture: Pigeonhole principle6m
Practical: Implementing the pigeonhole principle 9m
1 reading
Programming Homework 2 Instructions (Read First)10m
2 practice exercises
Module 230m
Programming Homework 230m
Week
3

Week 3

3 hours to complete

Edit distance, assembly, overlaps

3 hours to complete
13 videos (Total 92 min), 1 reading, 2 quizzes
13 videos
Lecture: Solving the edit distance problem12m
Lecture: Using dynamic programming for edit distance12m
Practical: Implementing dynamic programming for edit distance 6m
Lecture: A new solution to approximate matching9m
Lecture: Meet the family: global and local alignment10m
Practical: Implementing global alignment 8m
Lecture: Read alignment in the field4m
Lecture: Assembly: working from scratch2m
Lecture: First and second laws of assembly8m
Lecture: Overlap graphs8m
Practical: Overlaps between pairs of reads 4m
Practical: Finding and representing all overlaps 3m
1 reading
Programming Homework 3 Instructions (Read First)10m
2 practice exercises
Module 330m
Programming Homework 330m
Week
4

Week 4

3 hours to complete

Algorithms for assembly

3 hours to complete
13 videos (Total 83 min), 1 reading, 2 quizzes
13 videos
Lecture: The shortest common superstring problem8m
Practical: Implementing shortest common superstring 4m
Lecture: Greedy shortest common superstring7m
Practical: Implementing greedy shortest common superstring 7m
Lecture: Third law of assembly: repeats are bad5m
Lecture: De Bruijn graphs and Eulerian walks8m
Practical: Building a De Bruijn graph 4m
Lecture: When Eulerian walks go wrong9m
Lecture: Assemblers in practice8m
Lecture: The future is long?9m
Lecture: Computer science and life science5m
Lecture: Thank yous 43s
1 reading
Post Course Survey10m
2 practice exercises
Programming Homework 430m
Module 430m

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About the Genomic Data Science Specialization

Genomic Data Science

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