‘Inter‐Arrival Time’ Inspired Algorithm and its Application in Clustering and Molecular Phylogeny

Bioinformatics, being multidisciplinary field, involves applications of various methods from allied areas of Science for data mining using computational approaches. Clustering and molecular phylogeny is one of the key areas in Bioinformatics, which help in study of classification and evolution of organisms. Molecular phylogeny algorithms can be divided into distance based and character based methods. But most of these methods are dependent on pre‐alignment of sequences and become computationally intensive with increase in size of data and hence demand alternative efficient approaches. ‘Inter arrival time distribution’ (IATD) is a popular concept in the theory of stochastic system modeling but its potential in molecular data analysis has not been fully explored. The present study reports application of IATD in Bioinformatics for clustering and molecular phylogeny. The proposed method provides IATDs of nucleotides in genomic sequences. The distance function based on statistical parameters of IATDs is proposed and distance matrix thus obtained is used for the purpose of clustering and molecular phylogeny. The method is applied on a dataset of 3′ non‐coding region sequences (NCR) of Dengue virus type 3 (DENV‐3), subtype III, reported in 2008. The phylogram thus obtained revealed the geographical distribution of DENV‐3 isolates. Sri Lankan DENV‐3 isolates were further observed to be clustered in two sub‐clades corresponding to pre and post Dengue hemorrhagic fever emergence groups. These results are consistent with those reported earlier, which are obtained using pre‐aligned sequence data as an input. These findings encourage applications of the IATD based method in molecular phylogenetic analysis in particular and data mining in general.