https://www.sciencedaily.com/releases/2021/10/211004140305.htm

"This is one of the things that's really fascinating about mathematical research, is sometimes you can see connections between topics, which on the surface they seem so different, but at a mathematical level, they might be using some of the same technical ideas."

All of these questions involve mapping the likelihood of different variations on a biological theme: which combinations of mutations are most likely to arise in a particular protein, for example, or which chromosome mutations are most often found together in the same cancer cell. McCandlish explains that these are problems of density estimation -- a statistical tool that predicts how often an event happens. Density estimation can be relatively straightforward, such as charting different heights within a group of people. But when dealing with complex biological sequences, such as the hundreds, or thousands of amino acids that are strung together to build a protein, predicting the probability of each potential sequence becomes astonishingly complex.