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We arguably recognise three main approaches to generating new knowledge: experimental and theoretical research are classically the first two, while more recently computer simulations of natural phenomena (and of engineering artefacts) have contributed a third. Now Bell, Hey and Szalay have proposed a fourth – data-intensive science.
Continue reading: The fourth paradigm of scientific knowledge generation – data-intensive science
One of the fruits of the systematic sequencing of the human genome was the recognition (by bioinformatic sequence gazing) that there were a great many membrane-located receptors that had previously been unrecognized, and whose ‘natural’ roles and ligands were therefore unknown. These were and are known as orphan receptors (and G-protein-coupled receptors – GPCRs – represent a particularly rich class of such molecules, with several hundred members). Classically, receptors are recognized on the basis of binding studies (often of potent antagonists discovered in the natural world), and of physiological responses to candidate ligands. Clearly, with thousands of candidate endogenous small (metabolite) molecules (many probably as yet unknown, and some, possibly including DMT, derived from exogenous substances) it is not easy to test them all experimentally. How then to make progress?
Continue reading: Finding natural ligands for orphan receptors via cheminformatics
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