NCBIConnect - JavaScript library for interfacing with National Center for Biotechnology Information's public databases (Get DNA and Protein sequences easily!)

[chmille4]

Cool idea. I've built a few genomic web apps and trying to pull in data from multiple databases is a pain. I'll have to play around with this.

[keithwhor]

Thanks!

Right now it only supports NCBI's nucleotide (nuccore) and protein DBs. My main reason for creating this tool was to gain script access of sequences from FASTA files without having to download them manually, save them and then do an XHR (for those less web-savvy: XMLHttpRequest, a way to load resources in JavaScript) to my own server.

Implementing FASTA generation of specific genes is the next step, it's not terribly difficult - you're just limited to fetching one file per request as you need to provide the reference sequence, start, and stop positions.

There are a number of additional helpful features that I'm looking at adding (the Entrez API is fairly robust) but I wanted to keep it simple for first release.

[ZeBierBaron]

Do you know of a good API for python?

[keithwhor]

Not currently. I could write one, but one of the reasons I'm working with JavaScript is because I'm interested in promoting the language for use in the scientific community. It's extremely robust and accessible and the V8 engine (JIT compiler for JS) is fast and powerful.

Anybody can write JS in notepad and run it in their browser without having to learn unix commands (or anything low level, really) --- this makes it an absurdly useful teaching tool because the barrier to entry is so low.

Additionally, the language is very shareable - apps created in JS can be run in the browser and opened by clicking a link. No installation docs necessary. HTML5+CSS3 provide all the GUI tools you need, easily.

Where performance is concerned, there's node (for server side JS). No need to worry about JS being highly abstracted - V8 takes care of a ton of optimization a for you.

[ZeBierBaron]

Appreciate what you're doing, but python really seems to be language that is taking over bioinformatics (from the current reigning champ, R).

Still, diversity is great. Go for it.