An Efficient Computational Method of Motif Finding in the Zika Virus Genome

The Zika virus (ZIKV) outbreak and spread is a global health emergency declared by World Health Organization. ZIKV rapidly spread across the world, causing neurological disorders. It is gaining public and scientific consideration. ZIKV genome biology and molecular structure are better understood with published papers. Genetic regulation is better understood by finding the motif in the DNA Genome sequence. The transcription factor binding sites need to be identified to understand the genetic code. There is diversity in gene expression. Motif-finding methods work towards efficiently identifying the repeated patterns in the genome. ZIKV genome sequence is used in the study. Identifying the motif is still a difficult task. There is a low probability of identifying the binding sites. Finding all possible solutions is challenging as it requires a lot of time and has high space complexity for finding long motifs. The Greedy search technique with pseudocount finds the motif in real-time. The count matrix is computed, and the profile matrix is constructed from the genome of the Zika virus. The calculated consensus string helps in calculating the score of the motif. The Greedy motif search technique is applied in this paper to find the motifs in the Zika virus Genome. This technique is not applied earlier to find the motifs in Zika Virus. The motifs are identified using a Greedy motif search without pseudocount and with pseudocount.

@article{Mahapatro2022,
  title     = {An Efficient Computational Method of Motif Finding in the Zika Virus Genome},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {10},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Pushpa Susant Mahapatro and Jatinderkumar R. Saini},
  doi       = {10.14569/IJACSA.2022.0131014},
  url       = {https://doi.org/10.14569/IJACSA.2022.0131014}
}