Robust classification of subcellular location patterns in high resolution 3D fluorescence microscope images

Knowledge of a protein's subcellular location is essential to a complete understanding of its functions. Automated interpretation methods for protein location patterns are needed for proteomics projects, and we have previously described systems for classifying the major subcellular patterns in cultured mammalian cells. We describe here the calculation of improved 3D Haralick texture features, which yielded a near-perfect classification accuracy when combined with 3D morphological and edge features. In particular, a set of 7 features achieved 98% overall accuracy for classifying 10 major subcellular location patterns in HeLa cells.