Generation of digital patients for the simulation of tuberculosis with UISS-TB

Juárez, M.A. orcid.org/0000-0002-5128-0976, Pennisi, M., Russo, G. et al. (4 more authors) (2020) Generation of digital patients for the simulation of tuberculosis with UISS-TB. BMC Bioinformatics, 21 (S17). 449. ISSN 1471-2105

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Copyright, Publisher and Additional Information: © The Author(s) 2020. Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Keywords: Agent based model; In silico patient; Sequential sampling; Tuberculosis
Dates:
  • Accepted: 22 September 2020
  • Published (online): 14 December 2020
  • Published: 14 December 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 25 Jan 2021 16:36
Last Modified: 25 Jan 2021 16:36
Status: Published
Publisher: Springer Science and Business Media LLC
Refereed: Yes
Identification Number: https://doi.org/10.1186/s12859-020-03776-z
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