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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.
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
Certificate Available: Yes, Add a Verified Certificate for $49
Session: Course Starts on September 1, 2017
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.
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
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 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.
How To Join This Course
Go to the course website link
Create an edX account to SignUp
Choose “Register Now” to get started.
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