Prediction of mitochondrial proteins using discrete wavelet transform

A new method was proposed for prediction of mitochondrial proteins by the discrete wavelet transform, based on the sequence-scale similarity measurement. This sequence-scale similarity, revealing more information than other conventional methods, does not rely on subcellular location information and can directly predict protein sequences with different length. In our experiments, 499 mitochondrial protein sequences, constituting a mitochondria database, were used as training dataset, and 681 non-mitochondrial protein sequences were tested. The system can predict these sequences with sensitivity, specificity, accuracy and MCC of 50.30%, 95.74%, 76.53% and 0.54, respectively. Source code of the new program is available on request from the authors.