In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.
In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species. Our goal is to take small fragments of DNA from the individual and "map" them to the reference genome. We will see that the combinatorial pattern matching algorithms solving this problem are elegant and extremely efficient, requiring a surprisingly small amount of runtime and memory.
Read more
In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.
In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species. Our goal is to take small fragments of DNA from the individual and "map" them to the reference genome. We will see that the combinatorial pattern matching algorithms solving this problem are elegant and extremely efficient, requiring a surprisingly small amount of runtime and memory.
In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.
In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species. Our goal is to take small fragments of DNA from the individual and "map" them to the reference genome. We will see that the combinatorial pattern matching algorithms solving this problem are elegant and extremely efficient, requiring a surprisingly small amount of runtime and memory.
In the second half of the course, we will learn how to identify the function of a protein even if it has been bombarded by so many mutations compared to similar proteins with known functions that it has become barely recognizable. This is the case, for example, in HIV studies, since the virus often mutates so quickly that researchers can struggle to study it. The approach we will use is based on a powerful machine learning tool called a hidden Markov model.
Finally, you will learn how to apply popular bioinformatics software tools applying hidden Markov models to compare a protein against a related family of proteins.
What's inside
Syllabus
Week 1: Introduction to Read Mapping
Welcome to our class! We are glad that you decided to join us.
In this class, we will consider the following two central biological questions (the computational approaches needed to solve them are shown in parentheses):
- How Do We Locate Disease-Causing Mutations? (Combinatorial Pattern Matching)
- Why Have Biologists Still Not Developed an HIV Vaccine? (Hidden Markov Models)
As in previous courses, each of these two chapters is accompanied by a Bioinformatics Cartoon created by talented artist Randall Christopher and serving as a chapter header in the Specialization's bestselling print companion. You can find the first chapter's cartoon at the bottom of this message.
Read more
Syllabus
Welcome to our class! We are glad that you decided to join us.
In this class, we will consider the following two central biological questions (the computational approaches needed to solve them are shown in parentheses):
- How Do We Locate Disease-Causing Mutations? (Combinatorial Pattern Matching)
- Why Have Biologists Still Not Developed an HIV Vaccine? (Hidden Markov Models)
As in previous courses, each of these two chapters is accompanied by a Bioinformatics Cartoon created by talented artist Randall Christopher and serving as a chapter header in the Specialization's bestselling print companion. You can find the first chapter's cartoon at the bottom of this message.
Welcome to week 2 of the class!
This week, we will introduce a paradigm called the Burrows-Wheeler transform; after seeing how it can be used in string compression, we will demonstrate that it is also the foundation of modern read-mapping algorithms.
Welcome to week 3 of class!
Last week, we saw how the Burrows-Wheeler transform could be applied to multiple pattern matching. This week, we will speed up our algorithm and generalize it to the case that patterns have errors, which models the biological problem of mapping reads with errors to a reference genome.
Welcome to week 4 of class!
This week, we will start examining the case of aligning sequences with many mutations -- such as related genes from different HIV strains -- and see that our problem formulation for sequence alignment is not adequate for highly diverged sequences.
To improve our algorithms, we will introduce a machine-learning paradigm called a hidden Markov model and see how dynamic programming helps us answer questions about these models.
Welcome to week 5 of class!
Last week, we introduced hidden Markov models. This week, we will see how hidden Markov models can be applied to sequence alignment with a profile HMM. We will then consider some advanced topics in this area, which are related to advanced methods that we considered in a previous course for clustering.
Welcome to the sixth and final week of class!
This week brings our Application Challenge, in which we apply the HMM sequence alignment algorithms that we have developed.
Good to know
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Reviews summary
Compelling course on mutations in dna and proteins
Engaging topics include suffix trees, BWT, pattern matching, and HMMs.
Content is well-organized and helpful.
Course is a favorite among students.
Activities
Organize Course Materials
Show steps
Enhance comprehension through efficient organization of course materials.
Show steps
-
Create a dedicated folder or notebook for course materials.
-
Categorize and organize lecture slides, notes, readings, and other resources.
-
Use a consistent naming convention to easily locate files.
-
Review organized materials regularly to reinforce learning.
Review Bioinformatics Databases
Show steps
Refresh knowledge of bioinformatics databases to enhance information retrieval.
Browse courses on
Bioinformatics
Show steps
-
Visit popular bioinformatics databases such as NCBI GenBank and UniProt.
-
Explore different search options and filters to retrieve relevant data.
-
Practice downloading and analyzing sequence data.
Review: Designing Algorithms - A Computational Perspective
Show steps
Get an overview of useful data structures and algorithms typically used for combinatorial pattern matching.
View
Algorithm Design
on Amazon
Show steps
-
Read the table of contents and article summaries.
-
Read the first two chapters of each part.
-
Choose one particularly relevant chapter and read it in its entirety.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in a Study Group on HMMs
Show steps
Reinforce understanding of HMMs through collaborative engagement.
Browse courses on
Hidden Markov Models
Show steps
-
Join or form a study group with fellow learners.
-
Establish regular meeting times.
-
Choose a specific aspect of HMMs to focus on each session.
-
Work together to solve problems and deepen comprehension.
Follow Tutorials on Advanced Read Mapping Algorithms
Show steps
Expand knowledge of read mapping techniques for more accurate sequence alignment.
Browse courses on
Read Mapping
Show steps
-
Identify online tutorials or courses on advanced read mapping algorithms.
-
Select a tutorial that aligns with your learning goals.
-
Follow the tutorial, completing any exercises or assignments.
Practice Map-Reduce Problems
Show steps
Study combinatorial pattern matching in the context of map-reduce algorithms.
Show steps
-
Review the basic concepts of MapReduce.
-
Study how to use Hadoop or a similar framework to implement MapReduce programs.
-
Solve a series of practice problems involving combinatorial pattern matching using MapReduce.
Develop a Profile HMM for Protein Sequence Alignment
Show steps
Apply advanced concepts of HMMs and sequence alignment to protein analysis.
Browse courses on
Sequence Alignment
Show steps
-
Review the principles of profile HMMs and protein sequence alignment.
-
Choose a dataset of protein sequences and align them using a multiple sequence alignment tool.
-
Construct a profile HMM from the aligned sequences.
-
Use the profile HMM to align new protein sequences.
Create a Tutorial on Burrows-Wheeler Transform
Show steps
Enhance understanding through deeper engagement with the BWT.
Browse courses on
Burrows-Wheeler Transform
Show steps
-
Understand theoretical foundations of the Burrows-Wheeler Transform.
-
Choose and study an implementation of BWT in a programming language.
-
Create a step-by-step tutorial explaining the implementation and its applications.
Organize Course Materials
Show steps
Enhance comprehension through efficient organization of course materials.
Show steps
- Create a dedicated folder or notebook for course materials.
- Categorize and organize lecture slides, notes, readings, and other resources.
- Use a consistent naming convention to easily locate files.
- Review organized materials regularly to reinforce learning.
Review Bioinformatics Databases
Show steps
Refresh knowledge of bioinformatics databases to enhance information retrieval.
Browse courses on
Bioinformatics
Show steps
- Visit popular bioinformatics databases such as NCBI GenBank and UniProt.
- Explore different search options and filters to retrieve relevant data.
- Practice downloading and analyzing sequence data.
Review: Designing Algorithms - A Computational Perspective
Show steps
Get an overview of useful data structures and algorithms typically used for combinatorial pattern matching.
View
Algorithm Design
on Amazon
Show steps
- Read the table of contents and article summaries.
- Read the first two chapters of each part.
- Choose one particularly relevant chapter and read it in its entirety.
Participate in a Study Group on HMMs
Show steps
Reinforce understanding of HMMs through collaborative engagement.
Browse courses on
Hidden Markov Models
Show steps
- Join or form a study group with fellow learners.
- Establish regular meeting times.
- Choose a specific aspect of HMMs to focus on each session.
- Work together to solve problems and deepen comprehension.
Follow Tutorials on Advanced Read Mapping Algorithms
Show steps
Expand knowledge of read mapping techniques for more accurate sequence alignment.
Browse courses on
Read Mapping
Show steps
- Identify online tutorials or courses on advanced read mapping algorithms.
- Select a tutorial that aligns with your learning goals.
- Follow the tutorial, completing any exercises or assignments.
Practice Map-Reduce Problems
Show steps
Study combinatorial pattern matching in the context of map-reduce algorithms.
Show steps
- Review the basic concepts of MapReduce.
- Study how to use Hadoop or a similar framework to implement MapReduce programs.
- Solve a series of practice problems involving combinatorial pattern matching using MapReduce.
Develop a Profile HMM for Protein Sequence Alignment
Show steps
Apply advanced concepts of HMMs and sequence alignment to protein analysis.
Browse courses on
Sequence Alignment
Show steps
- Review the principles of profile HMMs and protein sequence alignment.
- Choose a dataset of protein sequences and align them using a multiple sequence alignment tool.
- Construct a profile HMM from the aligned sequences.
- Use the profile HMM to align new protein sequences.
Create a Tutorial on Burrows-Wheeler Transform
Show steps
Enhance understanding through deeper engagement with the BWT.
Browse courses on
Burrows-Wheeler Transform
Show steps
- Understand theoretical foundations of the Burrows-Wheeler Transform.
- Choose and study an implementation of BWT in a programming language.
- Create a step-by-step tutorial explaining the implementation and its applications.
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