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Prediction of protein function from its sequence is an important and challenging task in bioinformatics. The biological function of a protein primarily depends on the amino acid sequence within it. Identification of the amino acids (hot spots) that leads to the characteristic frequency signifying a particular biological function is really a tedious job in proteomic signal processing. In this paper we have proposed a new technique for identification of hot spots in proteins using an efficient time-frequency filtering approach known as the S-Transform filtering. The S-Transform is a powerful linear time-frequency representation and is especially useful for the filtering in the time-frequency domain. The potentiality of the new technique is analysed in identifying hot spots in proteins and the result obtained is compared with other existing methods. It reveals that the proposed method is superior to its counterparts and is consistent with results based on biological methodologies for identification of the hot spots. This new method also reveals some new hot spots which needs further investigation by the biological community.