Robust computer algorithms are required to interpret the
vast amounts of proteomic data currently being produced and to generate
generalized models which are applicable to ‘real world’ scenarios.
One such scenario is the classification of bacterial species. These
vary immensely, some remaining remarkably stable whereas others
are extremely labile showing rapid mutation and change. Such variation
makes clinical diagnosis difficult and pathogens may be easily
misidentified.