USING DISCRIMINANT FUNCTION FOR PREDICTION OF SUBCELLULAR LOCATION OFPROKARYOTIC PROTEINS

The discriminant function algorithm was introduced to predict the subc ellular location of proteins in prokaryotic organisms from their amino -acid composition. The rate of correct prediction for the three possib le subcellular locations of prokaryotic proteins studied by Reinhardt and Hubbard (Nucleic Acid Research, 1998, 26:2230-2236) was 90% by the self-consistency test, and 87% by the jackknife test. These rates are considerably higher than the results recently reported by them using the neural network method. Furthermore, the test procedure adopted her e is also more rigorous. The core of the current algorithm is the cova riance matrix, through which the collective interactions among differe nt amino-acid components of a protein can be reflected. It is anticipa ted that, owing to the intimate correlation of the function of a prote in with its subcellular location, the current algorithm mill become a useful tool for the systematic analysis of genome data. (C) 1998 Acade mic Press.