Protein Sequence in Classifying Dengue Serotypes

Abstract

Dengue is the growing disease. It serves, especially in children. Different diagnosing methods like ELISA, Platelia, haemaocytometer, RT-PCR, decision tree algorithms and recommender system with fuzzy logic are used to diagnose the dengue by blood specimen. But these methods identify severe cases after five to ten days of the person infected by dengue. Some other methods require saliva and urine samples instead of blood specimen when a volume of blood samples cannot be obtained from person, especially from children. But from this sample, the correct result could not be identified. To overcome these problems, this paper proposes dengue diagnosis method based on amino acids or components in the protein sequence as it needs only skin cells or hair or nail which can be collected easily from the patients. The proposed method not only diagnoses the dengue but also identifies serotypes using statistical analysis of protein sequence. The experimental results prove that the proposed method identifies dengue and its serotypes correctly by amino acids and components of protein sequences. The proposed method is capable of finding deficiency or dominance of amino acids or components in the dengue-infected protein sequence by assessing entropy, relative and weighted average values of amino acids or components.