Earlier this year I was involved in an excellent course run at the University by James Smith and Christoph Dessimoz on review writing for computational biology. It was practical and pragmatic, including aspects of review writing, critique and meta-analysis skills. A key part of the course was to write a review (with a colleague, in my case with the sharp and intelligent Hong Ge), submit it to a dummy journal and receive feedback from peers in the class. Each review was based on a lecture given by an invited speakers. Many of the talks were on molecular and genetic topics, such as protein-protein interactions or phylogenetic trees.

In some ways I was a bit of an outsider being from a neuroimaging and clinical background, but I began to realise the diverse background of others in the class and that really our techniques and methods had more similarities than differences.
And that’s how I ended up writing the first draft of what became this paper here examining the role microarray data could play in repurposing drugs. Francesco gave us an excellent lecture, and he and Julio helped me and Hong shape the ideas in to a draft that made some sort of sense! Francesco rightly takes the first author credits for starting the ball rolling and pulling the whole paper together.

I found the topic fascinating. You can take a damaged biological system and know very little about its mechanisms, but extract key information to help pick drugs already on the market (the process of repositioning or repurposing) and use them to correct the damage. In some ways it’s a shoot first, ask questions later approach. Two things really appeal, firstly the simplifying of a complex system to essential elements, secondly the pragmatic results focused methodology.

Simplifying complex systems is a major part of what I do to extract the key features of brain images. One has to remember that a brain scan is only a picture of the various bits of bone and fat, neuronal structures, synapses, neurotransmitters, genetic transcripts, electromagnetic fields and quantum interactions that make up the brain and head. Any measure we extract has to reflect as closely as possible the sum of part or all of these constituent parts. In the same way, microarray data of a diseased cell measures the broad and various working and damaged processes going on in that cell.

Of course it is important then to go on and understand the mechanisms involved, but the paper highlights that in this pragmatic approach it is not necessary if the goal is to find out whether the drug might work. I do sometimes feel like tearing my hair out when, as recently, another beta-amyloid focused drug fails, yet the drug

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