Two years ago David Searls published an article in PLoS Comp Bio describing a series of online courses in bioinformatics. Yesterday, the same author published an updated version, “A New Online Computational Biology Curriculum,” (PLoS Comput Biol 10(6): e1003662. doi: 10.1371/journal.pcbi.1003662).
This updated curriculum has a supplemental PDF describing hundreds of video courses that are foundational to a good understanding of computational biology and bioinformatics. The table of contents embedded into the PDF’s metadata (Adobe Reader: View>Navigation Panels>Bookmarks; Apple Preview: View>Table of Contents) breaks the curriculum down into 11 “departments” with links to online courses in each subject area:
- Mathematics Department
- Computer Science Department
- Data Science Department
- Chemistry Department
- Biology Department
- Computational Biology Department
- Evolutionary Biology Department
- Systems Biology Department
- Neurosciences Department
- Translational Sciences Department
- Humanities Department
Listings in the catalog can take one of three forms: Courses, Current Topics, or Seminars. All listed courses are video-based and free of charge, many being MOOCs offered by Coursera or edX.
More than just a link dump, the author of this paper has “road tested” most of the courses, having enrolled in up to a dozen at a time. Under each course listing the author offers commentary on the importance of the subject to a computational biology education and an opinion on the quality of instruction. (The author ranks in the top 50 students on Coursera in terms of the number of completed courses on Coursera!). For the courses that the author completed, listings have an “evaluation” section, which ranks the course in difficulty, time requirements, lecture/homework effectiveness, assessment quality, and overall opinions. The author also injects autobiographical annotations as to why he thinks the courses are useful in a bioinformatics career.
In summary, years of work went into creating this annotated course catalog, and is a great resource if you’re looking to get started in a computational biology career, or if you’re just looking to brush up on individual topics ranging from natural language processing to evolutionary theory.
To leave a comment
for the author, please follow the link and comment on his blog: Getting Genetics Done
offers daily e-mail updates
news and tutorials
on topics such as: visualization (ggplot2
), programming (RStudio
, Web Scraping
) statistics (regression
, time series
) and more...
If you got this far, why not subscribe for updates
from the site? Choose your flavor: e-mail
, or facebook