Research Data Leeds Repository

Dataset associated with "Stochastic dynamics of Francisella Tularensis infection and replication"

Citation

Carruthers, Jonathan and Lythe, Grant and López-García, Martín and Gillard, Joseph J. and Laws, Thomas R. and Lukaszewski, Roman and Molina-París, Carmen (2020) Dataset associated with "Stochastic dynamics of Francisella Tularensis infection and replication". University of Leeds. [Dataset] https://doi.org/10.5518/792¹

Dataset description

Python codes associated with "Stochastic dynamics of Francisella Tularensis infection and replication"

Subjects:	G000 - Mathematical sciences > G100 - Mathematics2
Divisions:	Faculty of Engineering and Physical Sciences > School of Mathematics3
Related resources:	Location Type https://eprints.whiterose.ac.uk/158287/4 Publication https://doi.org/10.1371/journal.pcbi.10077525 Publication
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	22 May 2020 11:47
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/6776
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Carruthers, Jonathan https://orcid.org/0000-0002-1372-32547 University of Leeds https://ror.org/024mrxd33 ror Lythe, Grant https://orcid.org/0000-0001-7966-55718 University of Leeds https://ror.org/024mrxd33 ror López-García, Martín https://orcid.org/0000-0003-3833-85959 University of Leeds https://ror.org/024mrxd33 ror Gillard, Joseph J. https://orcid.org/0000-0001-7486-892710 Defence Science and Technology Laboratory https://ror.org/04jswqb94 ror Laws, Thomas R. https://orcid.org/0000-0002-0142-916211 Defence Science and Technology Laboratory https://ror.org/04jswqb94 ror Lukaszewski, Roman https://orcid.org/0000-0003-1774-533512 Defence Science and Technology Laboratory https://ror.org/04jswqb94 ror Molina-París, Carmen https://orcid.org/0000-0001-9828-673713 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: Medical Research Council Grant numbers: MR/N014855/1 Publication date: 2020 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: jonty.carruthers@btinternet.com14 Last Modified: 20 Dec 2024 12:50

Files

Documentation

README [2kB] 15 README [2kB] 16 README [2kB] 17 Security: Anyone File name: README.txt18 Content type: Documentation Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 2kB

Program

FT ABC [6kB] 19 FT ABC [6kB] 20 FT ABC [6kB] 21 Security: Anyone File name: FT_ABC.py22 Content type: Program Description: Approximate Bayesian Computation rejection sampling algorithm to infer parameters of the agent-based model, from an in vivo study of Francisella tularensis infection in mice License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 6kB

FT Agent-based model [19kB] 23 FT Agent-based model [19kB] 24 FT Agent-based model [19kB] 25 Security: Anyone File name: FT_Agent-based_model.py26 Content type: Program Description: Simulates realisations of the agent-based model License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 19kB

FT Cohort analysis [7kB] 27 FT Cohort analysis [7kB] 28 FT Cohort analysis [7kB] 29 Security: Anyone File name: FT_Cohort_analysis.py30 Content type: Program Description: Uses the cohort analysis to reproduce the predictions in Fig 7 License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 7kB

• 1. https://doi.org/10.5518/792
• 2. https://archive.researchdata.leeds.ac.uk/view/subjects/G100.html
• 3. https://archive.researchdata.leeds.ac.uk/view/divisions/SM/
• 4. https://eprints.whiterose.ac.uk/158287/
• 5. https://doi.org/10.1371/journal.pcbi.1007752
• 6. https://archive.researchdata.leeds.ac.uk/id/eprint/677
• 7. https://orcid.org/0000-0002-1372-3254
• 8. https://orcid.org/0000-0001-7966-5571
• 9. https://orcid.org/0000-0003-3833-8595
• 10. https://orcid.org/0000-0001-7486-8927
• 11. https://orcid.org/0000-0002-0142-9162
• 12. https://orcid.org/0000-0003-1774-5335
• 13. https://orcid.org/0000-0001-9828-6737
• 14. mailto:jonty.carruthers@btinternet.com
• 15. https://archive.researchdata.leeds.ac.uk/677/4/README.txt
• 16. https://archive.researchdata.leeds.ac.uk/677/4/README.txt
• 17. https://archive.researchdata.leeds.ac.uk/677/4/README.txt
• 18. https://archive.researchdata.leeds.ac.uk/677/4/README.txt
• 19. https://archive.researchdata.leeds.ac.uk/677/1/FT_ABC.py
• 20. https://archive.researchdata.leeds.ac.uk/677/1/FT_ABC.py
• 21. https://archive.researchdata.leeds.ac.uk/677/1/FT_ABC.py
• 22. https://archive.researchdata.leeds.ac.uk/677/1/FT_ABC.py
• 23. https://archive.researchdata.leeds.ac.uk/677/2/FT_Agent-based_model.py
• 24. https://archive.researchdata.leeds.ac.uk/677/2/FT_Agent-based_model.py
• 25. https://archive.researchdata.leeds.ac.uk/677/2/FT_Agent-based_model.py
• 26. https://archive.researchdata.leeds.ac.uk/677/2/FT_Agent-based_model.py
• 27. https://archive.researchdata.leeds.ac.uk/677/3/FT_Cohort_analysis.py
• 28. https://archive.researchdata.leeds.ac.uk/677/3/FT_Cohort_analysis.py
• 29. https://archive.researchdata.leeds.ac.uk/677/3/FT_Cohort_analysis.py
• 30. https://archive.researchdata.leeds.ac.uk/677/3/FT_Cohort_analysis.py