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Protein fold classification is an important problem in bioinformatics and a challenging task for machine-learning algorithms. In this paper we present a solution which classifies protein folds using Kohonen's Self-Organizing Map (SOM) and a comparison between few approaches for protein fold classification. We use SOM, Fisher Linear Discriminant Analysis (FLD), K-Nearest Neighbour (KNN), Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) methods to classify three SCOP folds with sixdblp:conf/iwbbio/OzbudakD14 fatcat:qqm2ud32bvcobcrndudaam2oy4