Genomics and computational biology
Master
In Maynard (USA)
Description
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Type
Master
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Location
Maynard (USA)
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Start date
Different dates available
This course will assess the relationships among sequence, structure, and function in complex biological networks as well as progress in realistic modeling of quantitative, comprehensive, functional genomics analyses. Exercises will include algorithmic, statistical, database, and simulation approaches and practical applications to medicine, biotechnology, drug discovery, and genetic engineering. Future opportunities and current limitations will be critically addressed. In addition to the regular lecture sessions, supplementary sections are scheduled to address issues related to Perl, Mathematica and biology.
Facilities
Location
Start date
Start date
Reviews
Subjects
- Computational
- Genomics
- Engineering
- Biology
Course programme
Lectures: 1 sessions / week, 2 hours / session
Supplementary Sections: 5 sessions / term, 2 hours / session
Introductory courses in biology, computer science, and statistics. If you have any doubt about whether you have the equivalent experience, you should attend the appropriate sections which will focus on catching up with extra sections supplementing catch-up topics in greatest demand.
In addition to the lectures there will be section discussion meetings at the days and times above. Students will participate in at least one of those sections and form problem-solving and project teams consisting of at least one biology expert and one math/computer/engineering expert (or two to four people knowledgeable in both disciplines). Separate section on the basics of programming and molecular biology will be available in the first few weeks to even out the expected wide variation in backgrounds. Grades will be based on six problem sets, one final project, and participation in discussion sections covering the problems and about one scientific article per week. Your time commitment will be about 4 hours for classes and 6 to 12 additional hours per week, depending on background.
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Genomics and computational biology