@inproceedings{bioinflmu-1409,
  AUTHOR = {Schubö, Alexandra and Hadziahmetovic, Armin and Joppich, Markus and Zimmer, Ralf},
  TITLE = {{Collecting SARS-CoV-2 Encoded miRNAs via Text Mining}},
  BOOKTITLE = {Bioinformatics and Biomedical Engineering},
  YEAR = {2022},
  isbn = {978-3-031-07704-3},
  doi = {10.1007/978-3-031-07704-3_35},
  publisher = {Springer International Publishing},
  month = {June},
  pages = {429–441},
  url = {https://link.springer.com/chapter/10.1007/978-3-031-07704-3_35},
  abstract = {Established text mining approaches can be used to identify miRNAs mentioned in published papers and preprints. Here, we apply such a targeted approach to the LitCovid literature collection in order to find viral miRNAs published in connection to SARS-CoV-2. As LitCovid aims at being a comprehensive collection of literature on new findings on SARS-CoV-2 and the COVID-19 pandemic, it is perfectly suited for our goal of finding all reported SARS-CoV-2 miRNAs. The identified miRNAs provide an up-to-date and quite comprehensive collection of potential viral miRNAs, which is a useful resource for further research to fight the current pandemic.},
}