Journey to the Frontier of Computational Biology. Master bioinformatics software and computational approaches in modern biology.
About This 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!
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- Beginner Specialization.
- No prior experience required.
Finding Hidden Messages in DNA (Bioinformatics I)Upcoming session: Feb 26
- 4-10 hours/week
About the CourseNamed a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever ne
Genome Sequencing (Bioinformatics II)Upcoming session: Mar 12
- English, Chinese (Simplified)
About the CourseYou may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from b
Comparing Genes, Proteins, and Genomes (Bioinformatics III)Upcoming session: Mar 12
About the CourseOnce we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e
Molecular Evolution (Bioinformatics IV)Upcoming session: Mar 12
About the CourseIn 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 t
Genomic Data Science and Clustering (Bioinformatics V)Current session: Feb 19
About the CourseHow 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 algorit
Finding Mutations in DNA and Proteins (Bioinformatics VI)Upcoming session: Mar 12
About the CourseIn 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 indi
Bioinformatics Capstone: Big Data in BiologyUpcoming session: Mar 26
- 3 weeks of study, 3-4 hours/week
About the Capstone ProjectIn this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. In particular, in a series of App
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