University of California, San Diego is offering free online course on Introduction to Genomic Data Science. This course begins a series of classes illustrating the power of computing in modern biology.
Applicants will learn how to look for hidden messages in DNA without ever needing to put on a lab coat. This course will start on September 1, 2017.
User Review
( votes)Course At A Glance
Effort: 4 to 10 hours per week hour’s pw
Subject: Biology & Life Sciences
Institution: University of California, San Diego and edx
Languages: English
Price: Free
Certificate Available: Yes, Add a Verified Certificate for $49
Session: Course Starts on September 1, 2017
Providers’ Details
The University of California, San Diego (UC San Diego) is a student-centered, research-focused, service-oriented public institution that provides opportunity for all. This young university has made its mark regionally, nationally and internationally. Named in the top 15 research universities worldwide, UC San Diego fosters a culture of collaboration that sparks discoveries, advances society and drives economic impact.
About This Course
In the first half of this course, we’ll investigate DNA replication, and ask the question, where in the genome does DNA replication begin? You will learn how to answer this question for many bacteria using straightforward algorithms to look for hidden messages in the genome.
Why Take This Course?
In the second half of the course, we’ll examine a different biological question, and ask which DNA patterns play the role of molecular clocks. The cells in your body manage to maintain a circadian rhythm, but how is this achieved on the level of DNA? Once again, we will see that by knowing which hidden messages to look for, we can start to understand the amazingly complex language of DNA. Perhaps surprisingly, we will apply randomized algorithms to solve problems.
Finally, you will get your hands dirty and apply existing software tools to find recurring biological motifs within genes that are responsible for helping Mycobacterium tuberculosis go “dormant” within a host for many years before causing an active infection.
Learning Outcomes
- Write Python programs to solve various tasks you may encounter
- Formulate a formal computational problem from an informal biological problem
- Develop algorithms for solving computational problems
- Evaluate the effectiveness of algorithms
- Apply existing software to actual biological datasets
Instructors
Phillip Compeau
Phillip Compeau is an Assistant Teaching Professor in the Carnegie Mellon University Computational Biology Department, where he serves as Assistant Director of the Master’s in Computational Biology program.
Pavel Pevzner
Pavel Pevzner is Ronald R. Taylor Professor of Computer Science at the University of California, San Diego. He holds a Ph.D. from Moscow Institute of Physics and Technology, Russia.
Requirements
None
How To Join This Course
- Go to the course website link
- Create an edX account to SignUp
- Choose “Register Now” to get started.
- EdX offers honor code certificates of achievement, verified certificates of achievement, and XSeries certificates of achievement. Currently, verified certificates are only available in some courses.
- Once applicant sign up for a course and activate their account, click on the Log In button on the edx.org homepage and type in their email address and edX password. This will take them to the dashboard, with access to each of their active courses. (Before a course begins, it will be listed on their dashboard but will not yet have a “view course” option.)
