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The Zika virus (ZIKV) appeared as a significant universal health threat, requiring a comprehensive understanding of its genomic structure. With published articles, the molecular structure and genomic biology of ZIKV are well understood. Discovering the Deoxyribonucleic Acid (DNA) Genome sequence motif helps us understand genetic regulation better. Deciphering the genetic code requires identifying the transcription factor binding locations. The expression of genes varies. Motif identification techniques aim to effectively locate recurring patterns throughout the genome. The study is performed on the Zika virus genome sequence. Finding every motif is challenging because it takes more time and has more space complexity. This research uses the Gibbs Sampler method to recognize motifs in the ZIKV genome and illuminate critical aspects of its molecular structure and potential functional elements. Systematic analysis of genomic sequences that identified conserved motifs provided valuable insight into the underlying genetic patterns. The study uses advanced computational techniques to explore the complexity of the Zika virus genome, which will facilitate understanding its biological characteristics. The results advance fundamental knowledge of ZIKV genetics. For advancing our knowledge of ZIKV biology and for developing the targeted antiretroviral treatment, it is important to understand how these motifs function.

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A Novel Approach for Finding Motifs Using Efficient Computational Method in Genomic Insights into Zika Virus

  • 会议论文

  • 发表日期：

    2025年

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  • Pushpa Susant Mahapatro,
  • Jatinderkumar R. Saini,
  • Shraddha Vaidya

摘要

The Zika virus (ZIKV) appeared as a significant universal health threat, requiring a comprehensive understanding of its genomic structure. With published articles, the molecular structure and genomic biology of ZIKV are well understood. Discovering the Deoxyribonucleic Acid (DNA) Genome sequence motif helps us understand genetic regulation better. Deciphering the genetic code requires identifying the transcription factor binding locations. The expression of genes varies. Motif identification techniques aim to effectively locate recurring patterns throughout the genome. The study is performed on the Zika virus genome sequence. Finding every motif is challenging because it takes more time and has more space complexity. This research uses the Gibbs Sampler method to recognize motifs in the ZIKV genome and illuminate critical aspects of its molecular structure and potential functional elements. Systematic analysis of genomic sequences that identified conserved motifs provided valuable insight into the underlying genetic patterns. The study uses advanced computational techniques to explore the complexity of the Zika virus genome, which will facilitate understanding its biological characteristics. The results advance fundamental knowledge of ZIKV genetics. For advancing our knowledge of ZIKV biology and for developing the targeted antiretroviral treatment, it is important to understand how these motifs function.