These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
105 related articles for article (PubMed ID: 24510727)
1. Modeling HIV-1 dynamics and fitness in cell culture across scales. Immonen T; Somersalo E; Calvetti D Bull Math Biol; 2014 Feb; 76(2):486-514. PubMed ID: 24510727 [TBL] [Abstract][Full Text] [Related]
2. A Bayesian approach to parameter estimation in HIV dynamical models. Putter H; Heisterkamp SH; Lange JM; de Wolf F Stat Med; 2002 Aug; 21(15):2199-214. PubMed ID: 12210633 [TBL] [Abstract][Full Text] [Related]
3. A hybrid stochastic-deterministic computational model accurately describes spatial dynamics and virus diffusion in HIV-1 growth competition assay. Immonen T; Gibson R; Leitner T; Miller MA; Arts EJ; Somersalo E; Calvetti D J Theor Biol; 2012 Nov; 312():120-32. PubMed ID: 22814476 [TBL] [Abstract][Full Text] [Related]
4. Bayesian estimation of HIV-1 dynamics in vivo. Ushakova A; Pettersen FO; Mæland A; Lindqvist BH; Kvale D Math Med Biol; 2015 Mar; 32(1):38-55. PubMed ID: 24078026 [TBL] [Abstract][Full Text] [Related]
5. A mathematical model of cell-to-cell spread of HIV-1 that includes a time delay. Culshaw RV; Ruan S; Webb G J Math Biol; 2003 May; 46(5):425-44. PubMed ID: 12750834 [TBL] [Abstract][Full Text] [Related]
6. A stochastic model for early HIV-1 population dynamics. Tuckwell HC; Le Corfec E J Theor Biol; 1998 Dec; 195(4):451-63. PubMed ID: 9837702 [TBL] [Abstract][Full Text] [Related]
7. Bayesian inference for stochastic kinetic models using a diffusion approximation. Golightly A; Wilkinson DJ Biometrics; 2005 Sep; 61(3):781-8. PubMed ID: 16135029 [TBL] [Abstract][Full Text] [Related]
8. Markov chain Monte Carlo approach to parameter estimation in the FitzHugh-Nagumo model. Jensen AC; Ditlevsen S; Kessler M; Papaspiliopoulos O Phys Rev E Stat Nonlin Soft Matter Phys; 2012 Oct; 86(4 Pt 1):041114. PubMed ID: 23214536 [TBL] [Abstract][Full Text] [Related]
9. A gradient Markov chain Monte Carlo algorithm for computing multivariate maximum likelihood estimates and posterior distributions: mixture dose-response assessment. Li R; Englehardt JD; Li X Risk Anal; 2012 Feb; 32(2):345-59. PubMed ID: 21906114 [TBL] [Abstract][Full Text] [Related]
10. Modeling and estimation of kinetic parameters and replicative fitness of HIV-1 from flow-cytometry-based growth competition experiments. Miao H; Dykes C; Demeter LM; Cavenaugh J; Park SY; Perelson AS; Wu H Bull Math Biol; 2008 Aug; 70(6):1749-71. PubMed ID: 18648886 [TBL] [Abstract][Full Text] [Related]
11. Exploring heterogeneity in tumour data using Markov chain Monte Carlo. de Gunst MC; Dewanji A; Luebeck EG Stat Med; 2003 May; 22(10):1691-707. PubMed ID: 12720305 [TBL] [Abstract][Full Text] [Related]
12. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods. Lele SR; Dennis B; Lutscher F Ecol Lett; 2007 Jul; 10(7):551-63. PubMed ID: 17542934 [TBL] [Abstract][Full Text] [Related]
13. Monte Carlo estimates of natural variation in HIV infection. Heffernan JM; Wahl LM J Theor Biol; 2005 Sep; 236(2):137-53. PubMed ID: 16005307 [TBL] [Abstract][Full Text] [Related]
14. Approximate Bayesian computation (ABC) gives exact results under the assumption of model error. Wilkinson RD Stat Appl Genet Mol Biol; 2013 May; 12(2):129-41. PubMed ID: 23652634 [TBL] [Abstract][Full Text] [Related]
15. Generation of multicellular spatiotemporal models of population dynamics from ordinary differential equations, with applications in viral infection. Sego TJ; Aponte-Serrano JO; Gianlupi JF; Glazier JA BMC Biol; 2021 Sep; 19(1):196. PubMed ID: 34496857 [TBL] [Abstract][Full Text] [Related]
16. HIV with contact tracing: a case study in approximate Bayesian computation. Blum MG; Tran VC Biostatistics; 2010 Oct; 11(4):644-60. PubMed ID: 20457785 [TBL] [Abstract][Full Text] [Related]
17. Estimation of population pharmacokinetic parameters of saquinavir in HIV patients with the MONOLIX software. Lavielle M; Mentré F J Pharmacokinet Pharmacodyn; 2007 Apr; 34(2):229-49. PubMed ID: 17211713 [TBL] [Abstract][Full Text] [Related]
18. Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions. Frühwirth-Schnatter S; Pyne S Biostatistics; 2010 Apr; 11(2):317-36. PubMed ID: 20110247 [TBL] [Abstract][Full Text] [Related]
19. A dynamical study of a cellular automata model of the spread of HIV in a lymph node. Burkhead EG; Hawkins JM; Molinek DK Bull Math Biol; 2009 Jan; 71(1):25-74. PubMed ID: 18758865 [TBL] [Abstract][Full Text] [Related]
20. Stochastic differential equations as a tool to regularize the parameter estimation problem for continuous time dynamical systems given discrete time measurements. Leander J; Lundh T; Jirstrand M Math Biosci; 2014 May; 251():54-62. PubMed ID: 24631177 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]