Our sequencing analysis course ended last Friday, with an overwhelmingly positive response from the students. The few negative comments that I got were largely about organizational issues, and could be reshaped as suggestions for next time rather than as condemnations of this year's course.
The 23 students -- most with no …
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So, I've been teaching a course on next-generation sequence analysis for the last week, and one of the issues I had to deal with before I proposed the course was how to deal with the volume of data and the required computation.
You see, next-generation sequence analysis involves analyzing not …
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So, I'm running this summer course and I am trying to figure out how to organize the notes for students. I'd like to mix curriculum-specific notes ("here's what we're doing today, and here are some problems to work on") with tutorials (material independent of a single course, like "here's how …
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Inspired by the brilliant mind(s) behind python-commandments.org, here's a list of ideas you can use to help newbies learn Python!
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I've been doing some more focused bioinformatics programming recently, and as I'm thinking about how to teach biologists about data analysis, I realize more and more how much backstory goes into even relatively simple programming.
The problem: given a reference genome, and a very large set of short, error-prone, random …
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These days, molecular biologists are dealing with lots and lots of sequences, largely due to next-gen sequencing technologies. For example, the Illumina GA2 is producing 100-200 million DNA sequences, each of 75-125 bases, per run; that works out to 20 gb of sequence data per run, not counting metadata such …
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Analyzing Next-Generation Sequencing Data
May 31 - June 11th, 2010
Kellogg Biological Station, Michigan State University
CSE 891 s431 / MMG 890 s433, 2 cr
Applications are due by midnight EST, April 9th, 2010.
Course sponsor: Gene Expression in Disease and Development Focus Group at Michigan State University.
Instructors: Dr. C. Titus …
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