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A workflow for predicting MicroRNAs targets via accessibility in flavivirus genomes

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Abstract

Flavivirus infections are a serious public health issue in Brazil, particularly in recent years due to the large number and severity of cases of Zika and Dengue virus infections and, more recently, outbreaks of Yellow Fever virus infections. Therefore, understanding the effects of genetic variations at functional and structural levels and developing new tools are necessary for supporting arboviral surveillance and control efforts of these viruses. In this context, we developed a workflow to predict potential microRNA targets in Flavivirus genomes. The workflow implementation comprised the integration of Perl scripts, tools from ViennaRNA package, and miRanda software to search for potential microRNAs that potentially interact with non-coding regions of Flavivirus genomes. As a case study, genome sequences of Dengue virus serotypes were used. We could observe structural differences among the serotype sequences and miRNA target binding sites exclusively identified for each serotype, which may be useful for the development of diagnostic methods.

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APA

Valadares, A., Emília Walter, M., & Raiol, T. (2018). A workflow for predicting MicroRNAs targets via accessibility in flavivirus genomes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11228 LNBI, pp. 124–132). Springer Verlag. https://doi.org/10.1007/978-3-030-01722-4_12

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