Bioinformatics or B101nformatics

Yes, the title is true even if I do data science in bioinformatics, I don't do machine learning. As seen recently if used correctly, regressions tend to work as well as machine learning. Classic tools (?) still work, I can't say I have tried all of them, but they are quite useful. Also in bioinformatics it is hard to get a big number of samples to make both a good and reliable generalization and to train reliable a model with enough confidence. Last, most machine learning methods are to me black boxes, I don't understand them (yet). I like to understand what I use. (Although I can't say I have deeply understood the differences between some regression methods I use). Then, why I am writing this? Because it seems like an hype to say things like "powerful network medicine tools", "machine learning model", without explaining them in detail. So it becomes a black box, and science is not about black boxes. In science we want to increase the know...

Recently Google came up with Google Genomics  to store genomes and work with them. The easiest way to explore it is through their genome browser ( GA browser ).  Position 132564975 of chromosome 7 of genome HG01440 from the Google repository of the 1000 Genomes Project. Which are the next steps? For developers it has come up with a new API . The system is currently in open beta , so the income of comments and early adopters is going on. This is part of the feed back I want o give as well as some thoughts about it. Improve help pages In my experience a better documentation is better than a better version. What do I mean? I try to do more with less time, when I look for help I want a quick and easy (to follow) answer (if possible). Thats why Stack Overflow  has so many questions, or why the mailing list are open, to help more people with less effort. In fact the help is now divided between Stack Overflow' tag g oogle-genomics  and google-genomics-api...