The three-dimensional shape of a protein plays a key role in determining its function, so proteins in which particular atoms have very similar configurations in space often have similar functions. There is therefore a need for efficient methodology to identify, given two or more proteins represented by the coordinates of their atoms, subsets of those atoms which match within measurement error, after allowing for appropriate geometrical transformations to align the proteins. This chapter describes a Bayesian model-based methodology for such tasks, and presents several challenging applications.
|Title of host publication||The Oxford Handbook of Applied Bayesian Analysis|
|Editors||Anthony O'Hagan, Mike West|
|Publisher||Oxford University Press|
|Number of pages||24|
|Publication status||Published - May 2010|