One of the first organisms to be domesticated by humans was yeast. Saccharomyces yeast is remarkable because it can not only convert the glucose in grapes into ethanol (which we then consume as wine), but it can also invert its own metabolism, consuming the ethanol it just produced in a process called the diauxic shift. To find genes implicated in the diauxic shift, we will learn about clustering algorithms that will divide yeast genes into distinct groups based on their patterns of regulatory behavior.
A similar method can be applied to distinguish normal and tumor cells, an approach that led to diagnostic tests like MammaPrint for predicting the return of cancer after chemotherapy.
We can also apply clustering algorithms to identify the genetic foundation of human population structure and discover which populations have contributed to your own genome. To do so, we will need to power up the clustering algorithms we encounter using a powerful computational approach called principal component analysis.
How Did Yeast Become a Wine Maker? (Clustering Algorithms)
An Evolutionary History of Wine Making
Identifying Genes Responsible for the Diauxic Shift
Introduction to Clustering
The Lloyd Algorithm
Clustering Genes Implicated in the Diauxic Shift
Limitations of k-Means Clustering
From Coin Flipping to k-Means Clustering
Making Soft Decisions in Coin Flipping
Soft k-Means Clustering
Epilogue: Clustering Tumor Samples
What Genetic Characteristics Do Human Populations Share? (Principal Components Analysis)
Specific Content TBA
“Deciphering Molecular Evolution” is the suggested prerequisite for taking this course, but it is not a strict prerequisite, especially if you have some programming experience.
The programming assignments in this class can be solved using any programming language.
The printed course companion is Bioinformatics Algorithms: An Active-Learning Approach, by Compeau & Pevzner.
The majority of assessments for the course will consist of exercises and programming assignments. This course covers two chapters taken from Bioinformatics Algorithms: An Active Learning Approach, by Compeau & Pevzner.
Each chapter is also accompanied by a summary quiz and lecture videos.
Q: Will I get a statement of accomplishment after completing this class?
Yes. Students who successfully complete the class will receive a statement of accomplishment signed by the instructor.
Q: Can I receive a verified certificate for this course?
Yes. Students who would like a verified certificate can sign up for the course’s Signature Track option.
Q: I remember this course used to be part of the larger “Bioinformatics Algorithms (Part 2) course. Why was it split into three courses?
Based on survey feedback, completion data, and studies of other courses, we realized that having shorter courses gives our students more flexibility around their busy schedules. Even though the courses have been split, the overall content remains the same, so we feel confident that we’re maintaining learning standards of our material.
Q: What if I earned a voucher for retaking the old course? Can I use it in this course?
Vouchers from the older course will be valid for the courses “Deciphering Molecular Evolution” and “Finding Mutations in DNA and Proteins” but not for this course because it contains some new material.
Q: Does this mean that the overall cost for earning Verified Certificates in the course is greater now?
Yes. Since there are more courses now, the overall cost for Verified Certificates is greater than before. Coursera offers a Financial Aid program for learners who would face a serious hardship paying for our courses. Plus, if you just want to join and check out our course content, it’s still free and available to everyone.