I work in a lab (academic/genetics). We have a public facing website so when we develop tools they go there. So we're using: perl, java, R, python, php apart from the stuff we compile from c.
Stringy code thats hard to decipher can be written in any language I have discovered.
My take, Perl is kinda on the way out, though it was used extensively. BioPerl is a nice package.
Biologist like R, it pretty quick and behaves like they aren't programming. It can make graphs nicely.
Python seems to be the go to compromise. BioPerl is a really nice package. But people start to want to use it for big things and to get it performing adequately requires a lot. There is confusion from the researchers that scares them away: between python 2/3 numby, pypy. BioPython packages are pretty excellent.
If it needs to be fast and crunch large sets of data (fairly common) the tool is in C or C++. We should start using Rust..
We use Php (Silex) to deliver a front end and some quick database lookup and display. Its replacing perl for this.
Stringy code thats hard to decipher can be written in any language I have discovered.
My take, Perl is kinda on the way out, though it was used extensively. BioPerl is a nice package.
Biologist like R, it pretty quick and behaves like they aren't programming. It can make graphs nicely.
Python seems to be the go to compromise. BioPerl is a really nice package. But people start to want to use it for big things and to get it performing adequately requires a lot. There is confusion from the researchers that scares them away: between python 2/3 numby, pypy. BioPython packages are pretty excellent.
If it needs to be fast and crunch large sets of data (fairly common) the tool is in C or C++. We should start using Rust..
We use Php (Silex) to deliver a front end and some quick database lookup and display. Its replacing perl for this.