This course is part of the Bioinformatics Specialization

4.2
stars
88 ratings

Pavel Pevzner +1 more instructor

14,428 already enrolled

Offered By

Bioinformatics SpecializationUniversity of California San Diego

About this Course

3,253 recent views

How do we infer which genes orchestrate various processes in the cell?  How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters.
In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applied to gene expression data.

In the second half of the course, we will introduce another classic tool in data science called principal components analysis that can be used to preprocess multidimensional data before clustering in an effort to greatly reduce the number dimensions without losing much of the "signal" in the data.

Finally, you will learn how to apply popular bioinformatics software tools to solve a real problem in clustering.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 5 of 7 in the

Bioinformatics Specialization

Beginner Level

Approx. 9 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 5 of 7 in the

Bioinformatics Specialization

Beginner Level

Approx. 9 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.16/5 (6 Ratings)

Pavel Pevzner

Professor

Department of Computer Science and Engineering

706,467 Learners

14 Courses

Phillip Compeau

Visiting Researcher

Department of Computer Science & Engineering

233,862 Learners

8 Courses

Offered by

University of California San Diego

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

Syllabus - What you will learn from this course

Week1

Week 1

5 hours to complete

Week 1: Introduction to Clustering Algorithms

Welcome to class!At the beginning of the class, we will see how algorithms for clustering a set of data points will help us determine how yeast became such good wine-makers. At the bottom of this email is the Bioinformatics Cartoon for this chapter, courtesy of <a href="http://bearandfox.com" target="_blank" title="Link: http://bearandfox.com">Randall Christopher</a> and serving as a chapter header in the Specialization's bestselling <a href="http://bioinformaticsalgorithms.com" target="_blank">print companion</a>. How did the monkey lose a wine-drinking contest to a tiny mammal?  Why have Pavel and Phillip become cavemen? And will flipping a coin help them escape their eternal boredom until they can return to the present? Start learning to find out!<img width="550" alt="" src="http://bioinformaticsalgorithms.com/images/cover/clustering_cropped.jpg" title="Image: http://bioinformaticsalgorithms.com/images/cover/clustering_cropped.jpg">

5 hours to complete

5 videos (Total 33 min), 2 readings, 3 quizzes

Week2

Week 2

4 hours to complete

Week 2: Advanced Clustering Techniques

Welcome to week 2 of class!

This week, we will see how we can move from a "hard" assignment of points to clusters toward a "soft" assignment that allows the boundaries of the clusters to blend. We will also see how to adapt the Lloyd algorithm that we encountered in the first week in order to produce an algorithm for soft clustering. We will also see another clustering algorithm called "hierarchical clustering" that groups objects into larger and larger clusters.

4 hours to complete

5 videos (Total 35 min), 1 reading, 3 quizzes

Week3

Week 3

1 hour to complete

Week 3: Introductory Algorithms in Population Genetics

1 hour to complete

2 readings

Reviews

4.2

23 reviews

5 stars
52.27%
4 stars
28.40%
3 stars
10.22%
2 stars
3.40%
1 star
5.68%

TOP REVIEWS FROM GENOMIC DATA SCIENCE AND CLUSTERING (BIOINFORMATICS V)

by ZXJul 20, 2019

In depth and comprehensive coverage of the topics in genetic data analysis.

by JMMar 21, 2020

Really enjoyed the clustering chapters and the practical exercises with the yeast dataset

by DDOct 23, 2019

Truly awesome. What I liked best was that this course didn't have a peer reviewed final challenge, so I didn't have to wait months until my work was graded :)

by MKNov 10, 2018

Absolutely fantastic course. Kudos to the course creators.

View all reviews

About the Bioinformatics Specialization

Join Us in a Top 50 MOOC of All Time!

How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth? When you complete this Specialization, you will learn how to answer many questions in modern biology that have become inseparable from the computational approaches used to solve them. You will also obtain a toolkit of existing software resources built on these computational approaches and that are used by thousands of biologists every day in one of the fastest growing fields in science. Although this Specialization centers on computational topics, you do not need to know how to program in order to complete it. If you are interested in programming, we feature an "Honors Track" (called "hacker track" in previous runs of the course). The Honors Track allows you to implement the bioinformatics algorithms that you will encounter along the way in dozens of automatically graded coding challenges. By completing the Honors Track, you will be a bioinformatics software professional! Learn more about the Bioinformatics Specialization (including why we are wearing these crazy outfits) by watching our introductory video. You can purchase the Specialization's print companion, Bioinformatics Algorithms: An Active Learning Approach, from the textbook website. Our first course, "Finding Hidden Messages in DNA", was named a top-50 MOOC of all time by Class Central!

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Build employee skills, drive business results

Discover Coursera for Business

Genomic Data Science and Clustering (Bioinformatics V)

About this Course