1 Rougeron, V. et al. Chikungunya, a paradigm of neglected tropical disease that emerged to be a new health global risk. Journal of Clinical Virology 64, 144-152, doi:10.1016/j.jcv.2014.08.032 (2015).
2 Ross, R. W. The Newala epidemic: III. The virus: isolation, pathogenic properties and relationship to the epidemic. Journal of Hygiene 54, 177-191, doi:10.1017/S0022172400044442 (1956).
3 Thiberville, S.-D. et al. Chikungunya fever: Epidemiology, clinical syndrome, pathogenesis and therapy. Antiviral Research 99, 345-370, doi:10.1016/j.antiviral.2013.06.009 (2013).
4 Matusali, G. et al. Tropism of the Chikungunya Virus. Viruses 11, doi:10.3390/v11020175 (2019).
5 Couderc, T. et al. A mouse model for Chikungunya: young age and inefficient type-I interferon signaling are risk factors for severe disease. PLoS Pathog 4, e29, doi:10.1371/journal.ppat.0040029 (2008).
6 Hoarau, J. J. et al. Persistent chronic inflammation and infection by Chikungunya arthritogenic alphavirus in spite of a robust host immune response. Journal of immunology (Baltimore, Md. : 1950) 184, 5914-5927, doi:10.4049/jimmunol.0900255 (2010).
7 Zhang, X. et al. Differences in genome characters and cell tropisms between two chikungunya isolates of Asian lineage and Indian Ocean lineage. Virology journal 15, 130, doi:10.1186/s12985-018-1024-5 (2018).
8 Abere, B. et al. Proteomic analysis of chikungunya virus infected microgial cells. PLoS One 7, e34800, doi:10.1371/journal.pone.0034800 (2012).
9 Dhanwani, R. et al. Characterization of Chikungunya virus infection in human neuroblastoma SH-SY5Y cells: role of apoptosis in neuronal cell death. Virus research 163, 563-572, doi:10.1016/j.virusres.2011.12.009 (2012).
10 Abraham, R., Mudaliar, P., Padmanabhan, A. & Sreekumar, E. Induction of cytopathogenicity in human glioblastoma cells by chikungunya virus. PLoS One 8, e75854, doi:10.1371/journal.pone.0075854 (2013).
11 Lim, L. P., Glasner, M. E., Yekta, S., Burge, C. B. & Bartel, D. P. Vertebrate microRNA genes. Science 299, doi:10.1126/science.1080372 (2003).
12 Ding, S.-W. & Voinnet, O. Antiviral Immunity Directed by Small RNAs. Cell 130, 413-426, doi:10.1016/j.cell.2007.07.039 (2007).
13 Wienholds, E., Koudijs, M. J., van Eeden, F. J. M., Cuppen, E. & Plasterk, R. H. A. The microRNA-producing enzyme Dicer1 is essential for zebrafish development. Nat Genet 35, 217-218, doi:http://www.nature.com/ng/journal/v35/n3/suppinfo/ng1251_S1.html (2003).
14 Manni, I. et al. The microRNA miR-92 increases proliferation of myeloid cells and by targeting p63 modulates the abundance of its isoforms. The FASEB Journal 23, 3957-3966, doi:10.1096/fj.09-131847 (2009).
15 Lu, L.-F. & Liston, A. MicroRNA in the immune system, microRNA as an immune system. Immunology 127, 291-298, doi:10.1111/j.1365-2567.2009.03092.x (2009).
16 Wang, Y. & Lee, C. G. L. MicroRNA and cancer – focus on apoptosis. Journal of cellular and molecular medicine 13, 12-23, doi:10.1111/j.1582-4934.2008.00510.x (2009).
17 Cho, W. C. S. OncomiRs: the discovery and progress of microRNAs in cancers. Molecular Cancer 6, 60-60, doi:10.1186/1476-4598-6-60 (2007).
18 Hariharan, M., Scaria, V., Pillai, B. & Brahmachari, S. K. Targets for human encoded microRNAs in HIV genes. Biochemical and biophysical research communications 337, 1214-1218, doi:10.1016/j.bbrc.2005.09.183 (2005).
19 Ghosh, Z., Mallick, B. & Chakrabarti, J. Cellular versus viral microRNAs in host–virus interaction. Nucleic Acids Research 37, 1035-1048, doi:10.1093/nar/gkn1004 (2009).
20 Grundhoff, A. & Sullivan, C. S. Virus-encoded microRNAs. Virology 411, 325-343, doi:10.1016/j.virol.2011.01.002 (2011).
21 Stern-Ginossar, N. et al. Host Immune System Gene Targeting by a Viral miRNA. Science (New York, N.Y.) 317, 376-381, doi:10.1126/science.1140956 (2007).
22 Skalsky, R. L. & Cullen, B. R. Viruses, microRNAs, and Host Interactions. Annual review of microbiology 64, 123-141, doi:10.1146/annurev.micro.112408.134243 (2010).
23 Kincaid, R. P. & Sullivan, C. S. Virus-encoded microRNAs: an overview and a look to the future. PLoS Pathog 8, e1003018, doi:10.1371/journal.ppat.1003018 (2012).
24 Islam, M. S., Khan, M. A. A. K., Murad, M. W., Karim, M. & Islam, A. B. M. M. K. In silico analysis revealed Zika virus miRNAs associated with viral pathogenesis through alteration of host genes involved in immune response and neurological functions. Journal of medical virology 91, 1584-1594 (2019).
25 Pruitt, K. D. & Maglott, D. R. RefSeq and LocusLink: NCBI gene-centered resources. Nucleic Acids Res 29, doi:10.1093/nar/29.1.137 (2001).
26 Tempel, S. & Tahi, F. A fast ab-initio method for predicting miRNA precursors in genomes. Nucleic Acids Research 40, e80-e80, doi:10.1093/nar/gks146 (2012).
27 Tav, C., Tempel, S., Poligny, L. & Tahi, F. miRNAFold: a web server for fast miRNA precursor prediction in genomes. Nucleic Acids Res 44, W181-184, doi:10.1093/nar/gkw459 (2016).
28 Xue, C. et al. Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 6, 310, doi:10.1186/1471-2105-6-310 (2005).
29 Shen, W., Chen, M., Wei, G. & Li, Y. MicroRNA Prediction Using a Fixed-Order Markov Model Based on the Secondary Structure Pattern. PLOS ONE 7, e48236, doi:10.1371/journal.pone.0048236 (2012).
30 Gkirtzou, K., Tsamardinos, I., Tsakalides, P. & Poirazi, P. MatureBayes: A Probabilistic Algorithm for Identifying the Mature miRNA within Novel Precursors. PLOS ONE 5, e11843, doi:10.1371/journal.pone.0011843 (2010).
31 Kruger, J. & Rehmsmeier, M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 34, W451-454, doi:10.1093/nar/gkl243 (2006).
32 Aken, B. L. et al. The Ensembl gene annotation system. Database 2016, baw093-baw093, doi:10.1093/database/baw093 (2016).
33 Herrero, J. et al. Ensembl comparative genomics resources. Database 2016, bav096-bav096, doi:10.1093/database/bav096 (2016).
34 Ashburner, M. et al. Gene Ontology: tool for the unification of biology. Nat Genet 25, 25-29, doi:10.1038/75556 (2000).
35 Consortium, T. G. O. Gene Ontology Consortium: going forward. Nucleic Acids Research 43, D1049-D1056, doi:10.1093/nar/gku1179 (2015).
36 Kanehisa, M. et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res 36, D480-484, doi:10.1093/nar/gkm882 (2008).
37 Ogata, H. et al. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 27, 29-34 (1999).
38 Huang da, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4, 44-57, doi:10.1038/nprot.2008.211 (2009).
39 Huang da, W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37, 1-13, doi:10.1093/nar/gkn923 (2009).
40 Barrett, T. et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res 41, D991-995, doi:10.1093/nar/gks1193 (2013).
41 Saxena, T. et al. Combined miRNA and mRNA signature identifies key molecular players and pathways involved in chikungunya virus infection in human cells. PLoS One 8, e79886, doi:10.1371/journal.pone.0079886 (2013).
42 Nukui, M., Mori, Y. & Murphy, E. A. A Human herpesvirus 6A encoded miRNA: A role in viral lytic replication. J Virol, doi:10.1128/jvi.02007-14 (2014).
43 UniProt: the universal protein knowledgebase. Nucleic acids research 45, D158-D169, doi:10.1093/nar/gkw1099 (2017).