BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

211 related articles for article (PubMed ID: 24086517)

  • 1. Steady-state metabolite concentrations reflect a balance between maximizing enzyme efficiency and minimizing total metabolite load.
    Tepper N; Noor E; Amador-Noguez D; Haraldsdóttir HS; Milo R; Rabinowitz J; Liebermeister W; Shlomi T
    PLoS One; 2013; 8(9):e75370. PubMed ID: 24086517
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks.
    Hoppe A; Hoffmann S; Holzhütter HG
    BMC Syst Biol; 2007 Jun; 1():23. PubMed ID: 17543097
    [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. Genome-scale model for Clostridium acetobutylicum: Part II. Development of specific proton flux states and numerically determined sub-systems.
    Senger RS; Papoutsakis ET
    Biotechnol Bioeng; 2008 Dec; 101(5):1053-71. PubMed ID: 18767191
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A metabolite-centric view on flux distributions in genome-scale metabolic models.
    Riemer SA; Rex R; Schomburg D
    BMC Syst Biol; 2013 Apr; 7():33. PubMed ID: 23587327
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Pathway thermodynamics highlights kinetic obstacles in central metabolism.
    Noor E; Bar-Even A; Flamholz A; Reznik E; Liebermeister W; Milo R
    PLoS Comput Biol; 2014 Feb; 10(2):e1003483. PubMed ID: 24586134
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.
    Kiparissides A; Hatzimanikatis V
    Metab Eng; 2017 Jan; 39():117-127. PubMed ID: 27845184
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Enhanced flux prediction by integrating relative expression and relative metabolite abundance into thermodynamically consistent metabolic models.
    Pandey V; Hadadi N; Hatzimanikatis V
    PLoS Comput Biol; 2019 May; 15(5):e1007036. PubMed ID: 31083653
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Genome-scale model for Clostridium acetobutylicum: Part I. Metabolic network resolution and analysis.
    Senger RS; Papoutsakis ET
    Biotechnol Bioeng; 2008 Dec; 101(5):1036-52. PubMed ID: 18767192
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A Quantitative System-Scale Characterization of the Metabolism of Clostridium acetobutylicum.
    Yoo M; Bestel-Corre G; Croux C; Riviere A; Meynial-Salles I; Soucaille P
    mBio; 2015 Nov; 6(6):e01808-15. PubMed ID: 26604256
    [TBL] [Abstract][Full Text] [Related]  

  • 11. NExT: integration of thermodynamic constraints and metabolomics data into a metabolic network.
    Martínez VS; Nielsen LK
    Methods Mol Biol; 2014; 1191():65-78. PubMed ID: 25178784
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.
    McAnulty MJ; Yen JY; Freedman BG; Senger RS
    BMC Syst Biol; 2012 May; 6():42. PubMed ID: 22583864
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli.
    Bennett BD; Kimball EH; Gao M; Osterhout R; Van Dien SJ; Rabinowitz JD
    Nat Chem Biol; 2009 Aug; 5(8):593-9. PubMed ID: 19561621
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.
    Lee SH; Kim S; Kwon MA; Jung YH; Shin YA; Kim KH
    Biotechnol Bioeng; 2014 Dec; 111(12):2528-36. PubMed ID: 24942337
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Current state and challenges for dynamic metabolic modeling.
    Vasilakou E; Machado D; Theorell A; Rocha I; Nöh K; Oldiges M; Wahl SA
    Curr Opin Microbiol; 2016 Oct; 33():97-104. PubMed ID: 27472025
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Genome-scale reconstruction and in silico analysis of the Clostridium acetobutylicum ATCC 824 metabolic network.
    Lee J; Yun H; Feist AM; Palsson BØ; Lee SY
    Appl Microbiol Biotechnol; 2008 Oct; 80(5):849-62. PubMed ID: 18758767
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Thermodynamics-based metabolic flux analysis.
    Henry CS; Broadbelt LJ; Hatzimanikatis V
    Biophys J; 2007 Mar; 92(5):1792-805. PubMed ID: 17172310
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.
    Hamilton JJ; Dwivedi V; Reed JL
    Biophys J; 2013 Jul; 105(2):512-22. PubMed ID: 23870272
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Enzyme clustering accelerates processing of intermediates through metabolic channeling.
    Castellana M; Wilson MZ; Xu Y; Joshi P; Cristea IM; Rabinowitz JD; Gitai Z; Wingreen NS
    Nat Biotechnol; 2014 Oct; 32(10):1011-8. PubMed ID: 25262299
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.