Those involved in teaching bioinformatics may wish to check out or contribute to the efforts of the ICSB Education Committee who are seeking input to identify a consensus bioinformatics curriculum.
They’ve started a blog for this purpose, including a draft curriculum (.docx file) drawn from an initial survey.
With no disrespect to them the initial survey is limited given the large size of the field, being drawn from just 41 individuals. Nevertheless let’s briefly look at a few points raised.
They show a graph of responses to the question ’What are the most important topics that someone should understand in order to work in the field of computational biology / bioinformatics?’
I have to admit I don’t quite agree that programming and then statistics are the most important.
Let’s presume the student is already enrolled in a biology major. In that context programming and statistics are certainly important practical background that are unlikely to be covered by the rest of their courses.
A key element missing though, that I’ve touched on before, is the theoretical biology that is used in and underpins computational biology. To me that is the most important background. It is not necessarily taught much in ‘straight’ biology courses.
This naturally allies with the established techniques used in the field and with an understanding of how bioinformatics has developed. (Frequent readers here will know I believe it’s important to understand the history of your field.)
They suggest that the curriculum be broken into two broad topic areas:
- computation, mathematics and statistics (in yellow in the graph above)
- chemistry and biology (in blue in the graph above)
There was also a suggestion that ISMB’s topic areas be used as the topic areas for a curriculum (see .docx file).
Footnotes
I’d elaborate further, but perhaps readers are grateful I haven’t time! Feel free to add your thoughts in the comments.
Other articles on Code for life:
Teaching bioinformatics at high school
Choosing an algorithm — benchmarking bioinformatics
Research project coding v. end-user application coding
New bioinformatics journal — EMBnet.journal
Literate and test-driven programming (in bioinformatics)
Retrospective–The mythology of bioinformatics
Hello.
I quite agree with you. I don’t think programming and statistics are more important than biology or molecular chemistry (or the contrary).
But in fact, when you “do” bioinformatics every days, you search in databases, you calculate statistics on data and you program applications to do this quickly. But we sometime forget the objectives which is to test the hypothesis we proposed. And how can we propose hypothesis without theoretical biology ? As a computer scientist, I think I am not well prepared for such questions, that is why I work in strong collaboration with biologists and bio-chemists.
Bioinformatics is a field where biologists and computer scientists can (must) live in symbiosis. One can give its view to the other and, from this exchange, new ideas, new concepts then new tools can emerge.
During my phd, I lived in a bioinformatic lab, mostly computer science oriented. We were convinced that our tools and our ideas were of great use for biologists. Now, I live with only (bio)chemists around and I definitely not do the same research. Mostly because I must convince them that my tools are useful… and they show me that it is not always true. I think they opened my sight to the “real” stuff.