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“This is one of the things that is really fascinating in mathematical research is that sometimes you can see connections between subjects, which on the surface seem so different, but on a mathematical level, they could use 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 occur in a particular protein, for example, or which chromosomal mutations are most often found together in the same cancer cell. McCandlish explains that these are problems with estimating density, a statistical tool that predicts how often an event occurs. Estimating density can be relatively simple, such as plotting different heights within a group of people. But when it comes to complex biological sequences, such as the hundreds or thousands of amino acids that are linked together to build a protein, predicting the likelihood of each potential sequence becomes surprisingly complex.
McCandlish explains the fundamental problem his team uses mathematics to solve:
“Sometimes if you make, say, a mutation to a protein sequence, it doesn’t matter. The protein works well. And if you make a second mutation, it still works well, but then if you put the two together, now you have a broken protein. We have been trying to find ways to model not only the interactions between pairs of mutations, but between three or four or any number of mutations. “
The methods they developed can be used to interpret data from experiments that measure the impact of hundreds of thousands of different combinations of mutations on protein function.
This study, reported in the Proceedings of the National Academy of Sciences, began with conversations with two other CSHL colleagues: CSHL Fellow Jason sheltzer and associate professor Justin kinney. They worked with McCandlish to apply his methods to gene expression and the evolution of cancer mutations. Software released by McCandlish’s team will allow other researchers to use these same approaches in their own work. He says he hopes it will be applied to a variety of biological problems.
About the Cold Spring Harbor Lab
Founded in 1890, the Cold Spring Harbor Laboratory has shaped contemporary biomedical research and education with programs in cancer, neuroscience, plant biology, and quantitative biology. Home to eight Nobel Prize winners, the private, non-profit laboratory employs 1,100 people, including 600 scientists, students and technicians. For more information visit www.cshl.edu
SOURCE Cold Spring Harbor Laboratory
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