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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

125 related articles for article (PubMed ID: 25215847)

  • 1. Cause and cure of sloppiness in ordinary differential equation models.
    Tönsing C; Timmer J; Kreutz C
    Phys Rev E Stat Nonlin Soft Matter Phys; 2014 Aug; 90(2):023303. PubMed ID: 25215847
    [TBL] [Abstract][Full Text] [Related]  

  • 2. On the relationship between sloppiness and identifiability.
    Chis OT; Villaverde AF; Banga JR; Balsa-Canto E
    Math Biosci; 2016 Dec; 282():147-161. PubMed ID: 27789352
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Maximally informative next experiments for nonlinear models.
    McGee RL; Buzzard GT
    Math Biosci; 2018 Aug; 302():1-8. PubMed ID: 29709517
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Universally sloppy parameter sensitivities in systems biology models.
    Gutenkunst RN; Waterfall JJ; Casey FP; Brown KS; Myers CR; Sethna JP
    PLoS Comput Biol; 2007 Oct; 3(10):1871-78. PubMed ID: 17922568
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sloppiness: Fundamental study, new formalism and its application in model assessment.
    Jagadeesan P; Raman K; Tangirala AK
    PLoS One; 2023; 18(3):e0282609. PubMed ID: 36888634
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Bayesian parameter estimation for nonlinear modelling of biological pathways.
    Ghasemi O; Lindsey ML; Yang T; Nguyen N; Huang Y; Jin YF
    BMC Syst Biol; 2011; 5 Suppl 3(Suppl 3):S9. PubMed ID: 22784628
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Optimal sampling time selection for parameter estimation in dynamic pathway modeling.
    Kutalik Z; Cho KH; Wolkenhauer O
    Biosystems; 2004 Jul; 75(1-3):43-55. PubMed ID: 15245803
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Parameter synthesis in nonlinear dynamical systems: application to systems biology.
    Donzé A; Clermont G; Langmead CJ
    J Comput Biol; 2010 Mar; 17(3):325-36. PubMed ID: 20377448
    [TBL] [Abstract][Full Text] [Related]  

  • 9. SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.
    Zi Z; Klipp E
    Bioinformatics; 2006 Nov; 22(21):2704-5. PubMed ID: 16926221
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparing different ODE modelling approaches for gene regulatory networks.
    Polynikis A; Hogan SJ; di Bernardo M
    J Theor Biol; 2009 Dec; 261(4):511-30. PubMed ID: 19665034
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A data integration approach for cell cycle analysis oriented to model simulation in systems biology.
    Alfieri R; Merelli I; Mosca E; Milanesi L
    BMC Syst Biol; 2007 Aug; 1():35. PubMed ID: 17678529
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Ordinary differential equations with applications in molecular biology.
    Ilea M; Turnea M; Rotariu M
    Rev Med Chir Soc Med Nat Iasi; 2012; 116(1):347-52. PubMed ID: 23077920
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Likelihood-ratio test statistic for the finite-sample case in nonlinear ordinary differential equation models.
    Tönsing C; Steiert B; Timmer J; Kreutz C
    PLoS Comput Biol; 2023 Sep; 19(9):e1011417. PubMed ID: 37738254
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Experiment design through dynamical characterisation of non-linear systems biology models utilising sparse grids.
    Donahue MM; Buzzard GT; Rundell AE
    IET Syst Biol; 2010 Jul; 4(4):249-62. PubMed ID: 20632775
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Delineating parameter unidentifiabilities in complex models.
    Raman DV; Anderson J; Papachristodoulou A
    Phys Rev E; 2017 Mar; 95(3-1):032314. PubMed ID: 28415348
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Fides: Reliable trust-region optimization for parameter estimation of ordinary differential equation models.
    Fröhlich F; Sorger PK
    PLoS Comput Biol; 2022 Jul; 18(7):e1010322. PubMed ID: 35830470
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Modeling of nonlinear biological phenomena modeled by S-systems.
    Mansouri MM; Nounou HN; Nounou MN; Datta AA
    Math Biosci; 2014 Mar; 249():75-91. PubMed ID: 24524881
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Fast integration-based prediction bands for ordinary differential equation models.
    Hass H; Kreutz C; Timmer J; Kaschek D
    Bioinformatics; 2016 Apr; 32(8):1204-10. PubMed ID: 26685309
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Perspective: Sloppiness and emergent theories in physics, biology, and beyond.
    Transtrum MK; Machta BB; Brown KS; Daniels BC; Myers CR; Sethna JP
    J Chem Phys; 2015 Jul; 143(1):010901. PubMed ID: 26156455
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Scalable Inference of Ordinary Differential Equation Models of Biochemical Processes.
    Fröhlich F; Loos C; Hasenauer J
    Methods Mol Biol; 2019; 1883():385-422. PubMed ID: 30547409
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.