2019nCoVAS: Developing the web service for epidemic transmission prediction, genome analysis, and psychological stress assessment for 2019-nCoV

Ming Xiao, Guangdi Liu, Jianghang Xie, Zichun Dai, Zihao Wei, Ziyao Ren, Jun Yu, Le Zhang

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Since the COVID-19 epidemic is still expanding around the world and poses a serious threat to human life and health, it is necessary for us to carry out epidemic transmission prediction, whole genome sequence analysis, and public psychological stress assessment for 2019-nCoV. However, transmission prediction models are insufficiently accurate and genome sequence characteristics are not clear, and it is difficult to dynamically assess the public psychological stress state under the 2019-nCoV epidemic. Therefore, this study develops a 2019nCoVAS web service (http://www.combio-lezhang.online/2019ncov/home.html) that not only offers online epidemic transmission prediction and lineage-associated underrepresented permutation (LAUP) analysis services to investigate the spreading trends and genome sequence characteristics, but also provides psychological stress assessments based on such an emotional dictionary that we built for 2019-nCoV. Finally, we discuss the shortcomings and further study of the 2019nCoVAS web service.
Original languageEnglish
Article number9314878
Pages (from-to)1250-1261
Number of pages12
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume18
Issue number4
DOIs
Publication statusPublished - 1 Jul 2021

Keywords

  • 2019-nCoV
  • COVID-19
  • Epidemic prediction models
  • Genome analysis
  • LAUPs (lineage-associated underrepresented permutations)
  • Psychological stress assessment

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