Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution.
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| Title: | Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution. |
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| Authors: | Embacher PA; Department of Medical Physics & Biomedical Engineering, University College London, London, United Kingdom., Germanova TE; Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom., Roscioli E; Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom., McAinsh AD; Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom., Burroughs NJ; Mathematics Institute and Zeeman Institute, University of Warwick, Coventry, United Kingdom. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2022 Dec 27; Vol. 18 (12), pp. e1010765. Date of Electronic Publication: 2022 Dec 27 (Print Publication: 2022). |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1010765 |
