Tomorrow, May 14, 2022, is the Grand Final of the 66th Eurovision Song Contest, with hundreds of millions of fans across Europe (from Azerbaijan to Australia) spending their Saturday evening watching one of the greatest spectacles on television.

Proteomics and Machine Learning is an explosive combination. Explosive in the sense of rapidly expanding and with far-reaching impact.

As someone with allergies, fall is probably my favorite season. Especially on clear, sunny days.

Sixty years ago, or sixty-one to be precise, Emile Zuckerkandl, Richard T. Jones and Linus Pauling published a paper comparing patterns of hemoglobin tryptic peptides from different species. Ben Neely and I recently revisited this paper, and some of the literature following on this work, retracing the history of molecular phylogenetics and proteomics in very broad strokes.

It may have been the former professional ice hockey player and philanthropist Mats Sundin who in an interview first opened my eyes to the many analogies between professional sports and academic research, including of course the competitive personalities of elite athletes and researchers. There are also - unfortunately - many parallels between cheating in sports and scientific research. However, this is also where the stories diverge.

Would cutting the meter in half double your height? Would stretching the second make you faster than Usain Bolt? If you ask marketing people, the answer is yes.