Support vector machines for classification of homo-oligomeric proteins by incorporating subsequence distributions

Support vector machine approach is applied to classifying the protein homo-oligomers from the primary structure. For training and testing protein primary sequences, their subsequence distributions act as input vectors of support vector machine, therefore, the information of protein sequences is sufficiently taken into account. Our tests demonstrate that the residue order along protein sequences plays an important role in the recognition of the homo-oligomers, and the support vector machine method is an effective tool for the prediction of protein multimeric states. It was also confirmed that protein primary sequence encodes quaternary structure information.