A Java Program of Feature Extraction Algorithms for Protein Sequences

Shanping Qiao, Baoqiang Yan


Prediction of protein subcellular localizations attracted the eyes of many researchers and hence a serial of computational approaches which aimed at designing an effective learning machine to deal with the newly-found protein sequences on the base of the feature vector were developed in the last two decades. The feature extraction algorithm for protein sequences played a vital role actually. The information in the feature vector influenced the performance of the learning algorithm significantly. In order to facilitate users to build predicting system, three feature extraction algorithms about amino acid composition were introduced, improved and implemented in a Java program. By comparing the results with those from some web servers, it was proved that this program ran normally and had good performance both in time costing and user interface. Moreover, the results could be easily saved to the specified file for later use. It was anticipated that this program would give some help to researchers.


DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.4689


Protein Subcellular Location Prediction; Amino Acid Composition; Feature Extraction Algorithm; Java

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