MTB-GOA v5

There were still formal problems with MTB-GOA, so versions 4 and 5 came in close succession. This allowed adding some features to the software too and so, generally, wetted my coding appetite. No promises!

MTB-GOA v3

The third (charming) version has 87 duplicates removed and, more importantly, is the product of a Makefile. This means, the pipe is up on my side, and can now be fed further. Expect the next release not too soon.

Website up, MTB-GOA v2 too

We now have a web um page for what this blog is about, the MTBBASE where you will find links to most of the things mentioned here, and much more nicely than I can do it here---apologies for not tweaking the blogger look but you certainly see where time goes into. Version 2 of the annotations (hopefully) addresses most of what I got fed back from the UniProt-GOA group at EBI, notably evidence codes and usage of column 8. The same will make further releases necessary, also because guidelines are in flux.

M.tb. sulfur metabolism at reactome

Not the whole sulfur, but assimilation and cysteine biosynthesis pathways are now at reactome, and a picture too. So, what's next? On the human side, I'll tackle MoCo biosynthesis. On the bacillus, maybe look at which processes have most functional annotations and start from there?

Wow, quality control quite involved me again with programming, and prototyping with ruby is really fast. What takes time at this moment of learning a new language is the unexpected language details (say quirks), and of course, OO design. So, most quality rules I know of are applied. I'm now waiting for marks from the EBI GOA group, and further rules to apply. This means, yes, both the Indians and the EBI got the data now, as planned. Meanwhile, stalled work on M.tb pathways in reactome format continues.

900 papers

The numbers: 6,200 annotations of 899 papers about 2,306 proteins (58% of the genome)

So, it is done. Factum est. All papers until and including 2008 about Mycobacterium tuberculosis proteins (modulo some microarray-only and two-dozen without informative abstract) are annotated in GAF format. To achieve the last step, the correct format, I learned ruby and patched the bioruby package on the fly, which was fun---so I guess I stay with ruby (and bioruby) for some time.

Instead of doing The Right Thing[tm] now, which is quality control of the annotations, I'm thinking about fixing the GO parsing in bioruby. Guess what it will be.

just had to comment on an article from the 2009 Hindustan Times with an interesting story: an Indian expat wants to reestablish himself in his birth country. First thing he does, he writes a report and tries to capitalize all science assets he finds---without syncing with any political peers. Consequently, he is frowned upon and loses his job. Last I saw was his blog spewing one-sided information at his previous employer-to-be. Now, what does this tell the reader? First, before returning "home", check political compatibility; if not matching, first find peers with power before embarking on touchy subjects. It also proves having a standard scientific education does not create political sensibility in a person.

600 papers, 3700 annotations on 1600 genes!