I will start with a monthly post about bioinformatics. It might contain news from Spain, or whatever I heard about.
I personally agree with this long answer, which states that the problem is not the how we process information but, what we do with information. In genomics, metabolomics, interactomics, we don't need to process live streams of data, so technolgoy developed by Facebook, and Google towards solving this issues cannot be applied in -omics field.
But I must disagree with the author, I don't think GO or other efforts to understand the data add noise, only if wrongly used they add noise. But I must agree that there is such diversity of teams and purpose that it is very difficult to set a goal or create a standard procedure followed by everyone.
What do you think? Bioinformatics should use leading edge technology or invest more in how we can use information we already have?
Changed the machine room of Embl
Moving 20 Petabytes - blog post thanking the technical team @emblebi in the machine room move end of 2014. http://t.co/62nz6k8vwU
— Ewan Birney (@ewanbirney) January 13, 2015
Read Ewan's blog post to learn about this silent move.
I would also share this discussion from biostar:
Why the bioinformatics field don't move to the "leading edge technology for biology big data analysis"?
But I must disagree with the author, I don't think GO or other efforts to understand the data add noise, only if wrongly used they add noise. But I must agree that there is such diversity of teams and purpose that it is very difficult to set a goal or create a standard procedure followed by everyone.
What do you think? Bioinformatics should use leading edge technology or invest more in how we can use information we already have?