It is that time of the year again: NCBI has rolled out the new PubMed baseline, and it is my pleasure to present you with the latest and greatest of biomedical buzzwords. I present to you the BuzzCloud 2009 (click for a larger interactive version):
In case you have no idea what a BuzzCloud is, it is a visualization of some of the most trendy words in PubMed. To make a long story short, the size of the word represents how many times it was mentioned in the past, whereas the brightness represents how much it was mentioned in the year compared to the previous ten years. For more details, please refer to the original blog post.
The three largest words on the BuzzCloud 2009 are all reruns from earlier years: metagenomics and synthetic biology were both first seen on the BuzzCloud 2004) and click chemistry appeared in 2006. One can only conclude that these research areas continue to grow.
At the other end of the scale we have the small and bright words. These are the words that are rising most rapidly but have not appeared that many times in PubMed yet. Below are three selected examples that I think may be of particular interest to the readership of this blog.
Proteogenomics. Why we need a separate word for referring to the combination of proteomics and genomics is beyond me. There is even a paper on comparative proteogenomics published in Genome Research. One can only wonder when someone will compare metabolomics, proteomics, transcriptomics, and genomics data across environmental samples and coin the term comparative metametaboproteotranscriptogenomics.
Translational bioinformatics. Where bioinformatics meets clinical medicine (see blog post by Russ Altman). I think that bioinformaticians are indeed increasingly working on medically relevant data, which in my view is a good thing. It just makes me wonder what happened to medical informatics?
On a closing note, I am again pleasantly surprised how well the words picked up by a completely automated procedure fit with the ongoing activities in my lab. It is almost eerie.
This makes me wonder how many of the readers of this blog have published in the NAR database issue (not necessarily this year), and how many of you actually read what others publish there. I have thus set up a highly unscientific poll:
The terms many, some, and very few are obviously somewhat fuzzy. As a rough guideline, I would define many as >10 papers per issue, some as 5-10, and very few as <5.