When molecular biology courses have a mandatory requirement for basic information science (data down a noisy channel) that's when we'll be making real advances.
Ewan Birney, developer of ENSEMBL in an O'Reilly Network interview.
Bioinformatics is a rapidly growing field at the junction of molecular biology and computer science. The University of Puerto Rico is in need of expertise in this area, and has decided to develop a course to bootstrap new students into the area.
This course is being developed for Dr. Fernando Gonzalez from the UPR-RRP, and is designed to introduce the basic concepts involved in bioinformatics, using the programming language python. The course is targeted at advanced undergraduates or graduate students in computer or the natural sciences. The course is designed as a series of half-day sessions, combining a lecture introducing the material, and a laboratory exercise to give hands-on experience with the material. We plan to teach the course to 10-20 students over 5 Saturdays at the HPCf Teaching Lab. Students will be encouraged to install the software on their own computers and work on the Lab sessions during the week, or can come visit the HPCf.
We have selected python for this course. python is an interpreted, dynamically typed programming language that has many developers, and a growing reputation in scientific circles. The interpreted and dynamic nature of the language encourages interactive development, where the student can test out many computations and examine the results of each. Many packages for scientific computing are available for python, including biopython for sequence analysis tasks, mavric for phylogeny, MMTK for molecular modelling. The VMD program for molecular visualization allows complex visualizations to be scripted or automated using python. This means we can teach most of the course with only one language, concentrating on algorithms and fundamental principles, instead of programming mechanics. For the section on microarray analysis, we will use the R language in addition to python.
In addition to python, we will leverage many other free resources on the internet for this course, and teach the students to search for and take advantage of these resources for their own work. These resources include the VSNS BCD bioinformatics course, the free online book "Think Python", biopython, blast, clustalw, phylip, mavric, MMTK, VMD, and the R Project for Statistical Computing.
Lab session - Construct a multiple sequence alignment using biopython's interface to clustalw.
Lab session, use phylip and mavric to construct and display cladograms from the previous lab's sequence alignments.
Lab session - use MMTK to build a small protein and perform structural minimization.
Lab session - use VMD to render the structures we modelled in the previous session.
Humberto Ortiz Zuazaga
Most recent change: 2012/10/1 at 09:33
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