Note: this was written in 2009 so… out of date somewhat!
I’ve been asked several times about which computer skills are critical for bioinformatics. Important – note that I am just addressing the “computer skills” side of things here. This is my list for being a functional, comfortable bioinformatician.
- SQL and knowledge of databases. I always recommend that people start with MySQL, because it is crossplatform, very popular, and extremely well developed.
Perl or Python. Python wins now! (2017 update!) Preferably perl. It kills me to write this, because I like python so much more than perl, but from a “getting the most useful skills” perspective, I think you have to choose perl.
- basic Linux. Actually, being at a semi-sys admin level is even better. I always tell people to go “cold turkey” and just install Linux on their computer and commit to using it exclusively for a while. (Due to OpenOffice etc, this should be mostly doable these days). This will force a person to get comfortable. Learning to use a Mac from the command line is an ok second option, as is Solaris etc. Still, I’d have to say Linux would be preferred.
- basic bash shell scripting. There are still too many cases where this ends up being “just the thing to do”. And of course, this all applies to Mac.
- Some experience with Java or other “traditional languages” or a real understanding of modern programming paradigms. This may seem lame or vague. But it is important to understand how traditional programming languages approach problems. At minimum, this ensures some exposure to concepts like object-oriented programming, functional programming, libraries, etc. I know that one can get all of this with python and, yes, even perl – but I fear that some
many bioinformatics people get away without knowing these things to their detriment.
- R + Bioconductor. So many great packages in Bioconductor. Comfort with R can solve a lot of problems quickly. R is only growing; if I could buy stock in R, I would!
This may seem like a lot, but many of these items fit together very well. For example, one could go “cold turkey” and just use Linux and commit to doing bioinformatics by using a combination of R, perl and shell scripting, and an SQL-based database (MySQL). It is very common in bioinformatics to link these pieces, so… not so bad, in the end, I think.
As always, comments welcome…
Update: I just hired an experimental postdoc – thanks to all that applied – and I am temporarily suspending the search for a computational postdoc.
I’m looking for two postdocs: one computational (bioinformatics) postdoc and one molecular biology postdoc.
I just posted this ad to naturejobs, so here is the info:
2 Postdoctoral Positions Total
1 Computational (Bioinformatics) Postdoctoral Fellow
1 Experimental (Molecular Biology) Postdoctoral Fellow
These positions are in the laboratory of Mark Bieda. The lab focuses on (1) development of novel statistical and computational approaches to ChIP-seq and ChIP-chip data and (2) investigating the changes in chromatin marks in cancer using chromatin immunoprecipitation and related molecular biology approaches. These positions offer an excellent opportunity for cross-training (e.g. bioinformatics training for an experimentalist, experimental training for a computational postdoc).
Bioinformatics Position: The computational position will focus on novel statistical and algorithmic methods for analysis of microarray (ChIP-chip) and high-throughput sequencing (ChIP-seq) experiments. This project will afford the opportunity for large-scale experimental validation of predictions within the lab. The successful computational candidate will be comfortable thinking statistically and have good programming skills with a keen interest in large-scale data analysis. Experimental Position: The experimental position will focus on examining chromatin organization in brain tumor models (primarily gliomas). There is also opportunity for work on other projects in neurogenomics. Previous experience/familiarity with neuroscience is a plus, but not required. The successful candidate will have experience with a wide range of molecular biology techniques.
Both positions offer opportunities for both formal collaborative and informal interactions with other strong research groups, including a very active Brain Tumor Group at the university. The PI is committed to developing the careers of members of the laboratory.
The University of Calgary offers an excellent environment with a rapidly growing pool of biomedical research labs and significant shared facilities. We encourage all qualified persons to apply. The University of Calgary hires on the basis of merit and is committed to employment equity. However, Canadians and permanent residents of Canada will be given priority.
Calgary is a city of ~1 million people and is located only about 1.5 hours from world-renowned recreational areas (Banff and Jasper).
To apply, please send (1) cover letter, (2) CV and (3) names and contact information for three references to Aarif Edoo (email@example.com). PDF format for application materials is preferred. Letters should be addressed to Mark Bieda, Ph.D.