Developing programming experience for bioinformatics

[Mark]

I like Perl for scripting. It's powerful, very widely used, and has lots of online resources. I also think it's easy to learn to a level that will quickly make you productive. Many people seem to think Python is easy to learn, but the O'Reilly (a publisher of typically great computer books) book "Learning Python" is ~3 times longer than "Learning Perl" and doesn't even cover regular expressions. That's like a driving class that doesn't cover steering. I would steer away from this book if you choose Python. And of course a strong command of unix/linux is highly recommended though I would choose Perl or Python over extensive shell scripting.

[rnaseek]

I am biased and I would strongly encourage to start learning Python first and R as well. Lot of people find it easy to learn Python. Getting the hang of awesome unix commands would also be very useful.

Here are a few links to get started with R and Python

http://cmdlinetips.com/2011/09/free-python-books-online/

http://cmdlinetips.com/2011/11/free-r-books-online-for-beginners/

[Heisman]

I started teaching myself a year and a half ago (I'm a tech) and still consider myself a novice, so listen to others as well, but I have found that learning linux really well has been very beneficial. Getting a good understanding of how to write bash scripts as well as the basic linux commands (sed/tr/cut/sort/cat/paste/grep) in addition to learning a bit of awk has been tremendously useful for me.

[greenhilly]

I have an extensive molecular biology background but am relatively new to bioinformatics. Would like to extend my computational/programming skills to maximize utility in analyzing sequencing and other high-throughput data, as well as to improve my own marketability.

Many job postings refer to some combination of Perl/Python/C++/Java experience. Any suggestions regarding where to focus effort, particularly in a forward-looking manner?

Thanks for any suggestions.