Posts
Various pieces of work lately have pulled
me back into using the opensource stats package R. Having for years been a heavy JMP user it’s a
change. There’s a phenomenal breadth of packages and examples available on the
web for R users which means that whatever I’m trying to do, help is usually
only a few clicks away. And there’s a
philosophical point: by choosing to work in R I can just share a script,
knowing that whoever I share it with be able to run it, reproduce my work and if needed critique it, and as a working
scientist that matters. R has a
reputation for being a bit tough as a learning curve, but that’s proving
interesting. Being forced to think very
hard about what I’m doing is improving the quality of what I do, which in turn
brings me a paper that left me howling with laughter(in a good way). The
incomparable Pete Kenny has brought out a perspective piece on the quality of
analysis in many of the drug-likeness/property papers that have influenced
medicinal chemistry thinking over the last two decades. It’s a great read on why thinking hard
before doing really pays off. Enjoy.
Inflation
of correlation in the pursuit of drug-likeness Peter W. Kenny • Carlos
A. Montanari
J Comput
Aided Mol Des
