BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

215 related articles for article (PubMed ID: 26332243)

  • 1. Constructing kinetic models of metabolism at genome-scales: A review.
    Srinivasan S; Cluett WR; Mahadevan R
    Biotechnol J; 2015 Sep; 10(9):1345-59. PubMed ID: 26332243
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks.
    Saa PA; Nielsen LK
    Biotechnol Adv; 2017 Dec; 35(8):981-1003. PubMed ID: 28916392
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiological constraints.
    Chakrabarti A; Miskovic L; Soh KC; Hatzimanikatis V
    Biotechnol J; 2013 Sep; 8(9):1043-57. PubMed ID: 23868566
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations.
    Al-Subeihi AA; Alhusainy W; Kiwamoto R; Spenkelink B; van Bladeren PJ; Rietjens IM; Punt A
    Toxicol Appl Pharmacol; 2015 Mar; 283(2):117-26. PubMed ID: 25549870
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics.
    Haiman ZB; Zielinski DC; Koike Y; Yurkovich JT; Palsson BO
    PLoS Comput Biol; 2021 Jan; 17(1):e1008208. PubMed ID: 33507922
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Applications of kinetic modeling to plant metabolism.
    Rohwer JM
    Methods Mol Biol; 2014; 1083():275-86. PubMed ID: 24218221
    [TBL] [Abstract][Full Text] [Related]  

  • 7. k-Cone analysis: determining all candidate values for kinetic parameters on a network scale.
    Famili I; Mahadevan R; Palsson BO
    Biophys J; 2005 Mar; 88(3):1616-25. PubMed ID: 15626710
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Parameter estimation of in silico biological pathways with particle filtering towards a petascale computing.
    Nakamura K; Yoshida R; Nagasaki M; Miyano S; Higuchi T
    Pac Symp Biocomput; 2009; ():227-38. PubMed ID: 19209704
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties.
    Miskovic L; Béal J; Moret M; Hatzimanikatis V
    PLoS Comput Biol; 2019 Aug; 15(8):e1007242. PubMed ID: 31430276
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Use of randomized sampling for analysis of metabolic networks.
    Schellenberger J; Palsson BØ
    J Biol Chem; 2009 Feb; 284(9):5457-61. PubMed ID: 18940807
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Flux balance analysis of biological systems: applications and challenges.
    Raman K; Chandra N
    Brief Bioinform; 2009 Jul; 10(4):435-49. PubMed ID: 19287049
    [TBL] [Abstract][Full Text] [Related]  

  • 12. iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.
    Andreozzi S; Miskovic L; Hatzimanikatis V
    Metab Eng; 2016 Jan; 33():158-168. PubMed ID: 26474788
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Model reduction and a priori kinetic parameter identifiability analysis using metabolome time series for metabolic reaction networks with linlog kinetics.
    Nikerel IE; van Winden WA; Verheijen PJ; Heijnen JJ
    Metab Eng; 2009 Jan; 11(1):20-30. PubMed ID: 18718548
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Towards kinetic modeling of global metabolic networks: Methylobacterium extorquens AM1 growth as validation.
    Ao P; Lee LW; Lidstrom ME; Yin L; Zhu X
    Sheng Wu Gong Cheng Xue Bao; 2008 Jun; 24(6):980-94. PubMed ID: 18807980
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Filling kinetic gaps: dynamic modeling of metabolism where detailed kinetic information is lacking.
    Resendis-Antonio O
    PLoS One; 2009; 4(3):e4967. PubMed ID: 19305506
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Monte-Carlo modeling of the central carbon metabolism of Lactococcus lactis: insights into metabolic regulation.
    Murabito E; Verma M; Bekker M; Bellomo D; Westerhoff HV; Teusink B; Steuer R
    PLoS One; 2014; 9(9):e106453. PubMed ID: 25268481
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Rites of passage: requirements and standards for building kinetic models of metabolic phenotypes.
    Miskovic L; Tokic M; Fengos G; Hatzimanikatis V
    Curr Opin Biotechnol; 2015 Dec; 36():146-53. PubMed ID: 26342586
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian kinetic modeling for tracer-based metabolomic data.
    Zhang X; Su Y; Lane AN; Stromberg AJ; Fan TWM; Wang C
    BMC Bioinformatics; 2023 Mar; 24(1):108. PubMed ID: 36949395
    [TBL] [Abstract][Full Text] [Related]  

  • 19. In silico analysis of SNPs and other high-throughput data.
    Jamshidi N; Vo TD; Palsson BO
    Methods Mol Biol; 2007; 366():267-85. PubMed ID: 17568130
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Kinetic Monte Carlo simulation of the initial phases of chlorophyll fluorescence from photosystem II.
    Guo Y; Tan J
    Biosystems; 2014 Jan; 115():1-4. PubMed ID: 24176766
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.