A multilevel hierarchical framework for quantification of experimental heterogeneity in population snapshot data.
Saved in:
| Title: | A multilevel hierarchical framework for quantification of experimental heterogeneity in population snapshot data. |
|---|---|
| Authors: | Warne DJ; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia., Zhu X; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia., Steele TP; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia., Johnston ST; School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia., Sisson SA; School of Mathematics and Statistics, University of New South Wales, Sydney, Australia., Faria M; Department of Biomedical Engineering, The University of Melbourne, Melbourne, Australia., Murphy RJ; School of Mathematical Sciences, Adelaide University, Adelaide, Australia., Browning AP; School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia.; Mathematical Institute, University of Oxford, Oxford, United Kingdom. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2026 Jun 15; Vol. 22 (6), pp. e1014379. Date of Electronic Publication: 2026 Jun 15 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| 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 |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1553-7358 |
|---|---|
| DOI: | 10.1371/journal.pcbi.1014379 |
