Genomics, transcriptomics, proteomics, and metabolomics now meet paperomics: Automated trawling, not of whole slices of nature, but of whole slices of the scientific literature — the idea is to look for indirect links among papers that may indicate undiscovered links in nature.
From the Computable Genomix website:
…Powered by patent pending next generation text mining technology, GeneIndexer rapidly interrogates the scientific literature to extract both explicit and implicit gene associations….
Here’s a scientist’s comment: …this is a lot of fun to play with, it’s simple to use and it actually bloody works.
Laika’s MedLibLog discusses the opacity of today’s biomedical literature, asking “Will Nano-Publications & Triplets Replace The Classic Journal Articles?” Behind this is the question, “Why bury data first and then mine it again?”
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This kind of data mining is fascinating. So far as I know the first major examples came from Don Swanson’s work back in the late 1980s, see:
http://scholar.google.ca/scholar?hl=en&q=DR+Swanson
His papers on Raynaud’s syndrome is a classic; he also wrote several later survey papers describing progress after the paper on Raynaud’s syndrome. E.g.: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC225324/