>Beautiful examples in theory, but blown out of the water in practice I will admit that this work was largely done 10 years ago, so it's certainly a bit outdat

>Beautiful examples in theory, but blown out of the water in practice I will admit that this work was largely done 10 years ago, so it's certainly a bit outdated. I will also concede that the current state of affairs in antimicrobials research is dreadful. >Can anyone offer a practical example of how bioinformatics has genuinely been (pref. statistically) useful in successful drug discovery? I can offer no data that stands up to a rigorous statistical analysis that you seek as far as bioinformatics impact on drug discovery is concerned. This is the primary reason most of us with bioinformatics experience who used to work in the pharma industry don't work there anymore (and for a great many of us this was not by choice). >As such, I find it awkward and outdated to claim that novel drug discovery is a great testament to phylogenetics and bioinformatics. Where did I make this claim? I chose the examples I did (which are real and actual examples by the way) of the way one can use phylogenetics to point out to the parent poster that it's not all crusty old geezers arguing about whether two almost indistinguishable variants of mice are part of the same taxon (which is the view a great many people who have never worked in the field often have). I chose these examples because they are practical examples of phylogenetic techniques that are easy to explain in a forum such as this in a few paragraphs. I can't speak to the viral one, as I was only peripherally involved in that work, but my very first job was taking bacterial sequences, making alignments, and looking at the phylogenetic trees to see whether or not they were too close to eukaryotes for comfort. This was the policy of the company where I worked: the antimicrobials team wanted to ensure both spectrum (that targets they were going after were actually present in medically important bugs) and specificity (that they weren't sloppy targets that you might accidentally hit a human enzyme with). There were a great many targets that I personally de-prioritized because they were no good purely from an informatics perspective.