Molecular Evolution (Bioinformatics IV) from Coursera

In the previous course in the Specialization, we learned how to compare genes, proteins, and genomes. One way we can use these methods is in order to construct a "Tree of Life" showing how a large collection of related organisms have evolved over time.

In the first half of the course, we will discuss approaches for evolutionary tree construction that have been the subject of some of the most cited scientific papers of all time, and show how they can resolve quandaries from finding the origin of a deadly virus to locating the birthplace of modern humans.

In the second half of the course, we will shift gears and examine the old claim that birds evolved from dinosaurs. How can we prove this? In particular, we will examine a result that claimed that peptides harvested from a T. rex fossil closely matched peptides found in chickens. In particular, we will use methods from computational proteomics to ask how we could assess whether this result is valid or due to some form of contamination.

Finally, you will learn how to apply popular bioinformatics software tools to reconstruct an evolutionary tree of ebolaviruses and identify the source of the recent Ebola epidemic that caused global headlines.

What's inside

Syllabus

Week 1: Introduction to Evolutionary Tree Construction

Welcome to our class!

In this class, we will consider the following two central biological questions (the computational approaches needed to solve them are shown in parentheses):

Weeks 1-3: Which Animal Gave Us SARS? (Evolutionary tree construction)
Weeks 4-5: Was T. rex Just a Big Chicken? (Combinatorial Algorithms)

In Week 6, you will complete a Bioinformatics Application Challenge to apply evolutionary tree construction algorithms in order to determine the origin of the recent ebola outbreak in Africa.

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. What do stick bugs and bats have to do with deadly viruses? And how can bioinformatics be used to stop these viruses in their tracks? Start learning today and find out!

Image: http://bioinformaticsalgorithms.com/images/cover/evolution_cropped.jpg

Week 2: More Algorithms for Constructing Trees from Distance Matrices

Welcome to Week 2 of class!

Last week, we started to see how evolutionary trees can be constructed from distance matrices. This week, we will encounter additional algorithms for this purpose, including the neighbor-joining algorithm, which has become one of the top-ten most cited papers in all of science since its introduction three decades ago.

Week 3: Constructing Evolutionary Trees from Characters

Welcome to week 3 of class!

Over the last two weeks, we have seen several different algorithms for constructing evolutionary trees from distance matrices.

This week, we will conclude the current chapter by considering what happens if we use properties called "characters" instead of distances. We will also see how to infer the ancestral states of organisms in an evolutionary tree, and consider whether it is possible to define an efficient algorithm for this task.

Week 4

Welcome to week 4 of the class!

Did birds evolve from dinosaurs? Over the next two weeks, we will see how we could analyze molecular evidence in support of this theory. You can find this week's Bioinformatics Cartoon from Randall Christopher at the bottom of this E-mail. Why does the T. rex look so much like a chicken? And why is the monkey typing frantically? Keep learning to find out!

Image: http://bioinformaticsalgorithms.com/images/cover/proteomics_cropped.jpg

Week 5: Resolving the T. rex Peptides Mystery?

Welcome to week 5 of class!

Last week, we asked whether it is possible for dinosaur peptides to survive locked inside of a fossil for 65 million years. This week, we will see what this question has to do with statistics; in the process, we will see how a monkey typing out symbols on a typewriter can be used to address it.

Week 6: Bioinformatics Application Challenge

Welcome to the sixth and final week of the course!

In this week's Bioinformatics Application Challenge, we will use reconstruct an evolutionary tree of ebolaviruses and use it to determine the origin of the pathogen that caused the recent outbreak in Africa.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores phylogenetic principles and techniques used to study evolutionary relationships using distance methods

Examines the methodological considerations and statistical challenges in analyzing molecular sequences for evolutionary inference

Develops computational skills for understanding and constructing phylogenetic trees

Prerequisite knowledge in programming and data analysis is strongly recommended

May require additional software or resources for practical exercises

Reviews summary

Challenging bioinformatics elective

Learners say that Molecular Evolution (Bioinformatics IV) is a challenging but fun elective that is good for practicing algorithmic skills. The course material is of good quality and the code problems are engaging. However some learners mention that the peer review process can be difficult, especially when working with diagrams of poor quality.

Course is challenging but fun.

"Challenging but fun course!"

"Good course for improving algorithmic skills and keep learning something new"

Material is of good quality.

"Good course material and challenging code problems!"

Peer review can be difficult.

"Onde remark : the peer review was almost impossible to correct because the diagrams (trees) where of such lpoor quality that the numvers where almost completely unreadable!"

Career center

Learners who complete Molecular Evolution (Bioinformatics IV) will develop knowledge and skills that may be useful to these careers:

Computational Biologist

Computational Biologists use computational and mathematical techniques to study biological systems. They develop and apply algorithms and software to analyze and interpret large datasets, such as genetic sequences and protein structures. This course provides a strong foundation in the principles and algorithms of bioinformatics, which are essential for success in this field. Computational Biologists typically have a PhD degree in computational biology, computer science, or a related field.

See salaries and explore the career path for Computational Biologist

Bioinformatics Scientist

Bioinformatics Scientists develop and apply computational and analytical methods to solve biological problems. They use their knowledge of molecular biology, computer science, and statistics to analyze and interpret large datasets, such as genetic sequences and protein structures. This course provides a strong foundation in the principles and algorithms of bioinformatics, which are essential for success in this field. Bioinformatics Scientists typically have a master's or PhD degree in bioinformatics, computer science, or a related field.

See salaries and explore the career path for Bioinformatics Scientist

Data Scientist

Data Scientists use their knowledge of statistics, computer science, and business to analyze and interpret large datasets. They develop and apply algorithms and software to extract insights from data and make predictions. This course provides a strong foundation in the principles and algorithms of bioinformatics, which can be applied to a wide range of data science problems. Data Scientists typically have a master's or PhD degree in data science, computer science, or a related field.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use their knowledge of probability and statistics to analyze and interpret data. They develop and apply statistical methods to solve problems in a wide range of fields, including biology, medicine, and finance. This course provides a strong foundation in the principles and algorithms of bioinformatics. Statisticians typically have a master's or PhD degree in statistics.

See salaries and explore the career path for Statistician

Software Engineer

Software Engineers design, develop, and maintain software applications. They use their knowledge of computer science to create software that meets the needs of users. This course provides a strong foundation in the principles and algorithms of bioinformatics. Software Engineers typically have a bachelor's or master's degree in computer science or a related field.

See salaries and explore the career path for Software Engineer

Biomedical Engineer

Biomedical Engineers design and develop medical devices and technologies. They use their knowledge of engineering and biology to create new ways to diagnose and treat diseases. This course provides a strong foundation in the principles and algorithms of bioinformatics, which are essential for success in this field. Biomedical Engineers typically have a bachelor's or master's degree in biomedical engineering or a related field.

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Genetic Counselor

Genetic Counselors provide information and support to individuals and families who are affected by genetic disorders. They use their knowledge of genetics and counseling to help people understand their risks and make informed decisions about their health. This course provides a strong foundation in the principles and algorithms of bioinformatics, which can be applied to a wide range of genetic counseling problems. Genetic Counselors typically have a master's degree in genetic counseling or a related field.

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Research Scientist

Research Scientists conduct scientific research in a variety of fields, including biology, chemistry, and physics. They use their knowledge to develop new theories and technologies. This course provides a strong foundation in the principles and algorithms of bioinformatics.

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