Algorithms for DNA Sequencing
Johns Hopkins University (JHU), United States
Language course is: English (subtitles for other languages)
Focus: Bioinformatics
Target audience education / assumed knowledge:
None
Educational certification/accreditation status:
None
Professional certification/accreditation status:
None
Degree Offered:
Course Certificate (1-3 mths)
Key characteristics of program:
This course is delivered online on the Coursera MOOC platform. It consists of: (a) about 1 hour of lectures per week by Prof. Langmead, (b) about 1 hour of practical lectures per week by Prof. Langmead and Jacob Pritt, (c) one multiple choice homework assignment per module, (d) one programming-based homework assignment per module and (e) some optional lectures covering a broader selection of research ideas.
This course is delivered online on the Coursera MOOC platform. It consists of: (a) about 1 hour of lectures per week by Prof. Langmead, (b) about 1 hour of practical lectures per week by Prof. Langmead and Jacob Pritt, (c) one multiple choice homework assignment per module, (d) one programming-based homework assignment per module and (e) some optional lectures covering a broader selection of research ideas.
Program Goals:
DNA sequencing is now a ubiquitous tool in life science. You can observe this trend just by reading the news. This course examines the computational problems that come with this onslaught of DNA sequencing data. How do we take a huge collection of DNA "puzzle pieces" and assemble them into a genome? How do we make it quick and easy to find a DNA "needle" in an enormous genomic "haystack"? We will spend the bulk of the course understanding the algorithms and data structures that underlie software tools for analyzing sequencing data. The course is also an opporunity to practice programming skills and gain exposure to basic algorithms and data structures.
DNA sequencing is now a ubiquitous tool in life science. You can observe this trend just by reading the news. This course examines the computational problems that come with this onslaught of DNA sequencing data. How do we take a huge collection of DNA "puzzle pieces" and assemble them into a genome? How do we make it quick and easy to find a DNA "needle" in an enormous genomic "haystack"? We will spend the bulk of the course understanding the algorithms and data structures that underlie software tools for analyzing sequencing data. The course is also an opporunity to practice programming skills and gain exposure to basic algorithms and data structures.
Additional Information
Year Program Established: 2016
Course/tuition costs: $49 (free without certificate)
Scholarships/assistanceships may be available: Yes
Average number of applicants per year: 15000
Average number of applicants accepted per year: 15000
Average number of incoming students per year: 15000
Average number of graduates per year: 1200
Program URL: http://www.coursera.org/course/ads1
Syllabus URL: http://www.coursera.org/course/ads1
Contact Person: Ben Langmead ( [javascript protected email address])
Last updated: Nov 12, 2015
Course/tuition costs: $49 (free without certificate)
Scholarships/assistanceships may be available: Yes
Average number of applicants per year: 15000
Average number of applicants accepted per year: 15000
Average number of incoming students per year: 15000
Average number of graduates per year: 1200
Program URL: http://www.coursera.org/course/ads1
Syllabus URL: http://www.coursera.org/course/ads1
Contact Person: Ben Langmead ( [javascript protected email address])
Last updated: Nov 12, 2015
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