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 *

120 related articles for article (PubMed ID: 36808187)

  • 21. Thermodynamic constraints for identifying elementary flux modes.
    Peres S; Schuster S; Dague P
    Biochem Soc Trans; 2018 Jun; 46(3):641-647. PubMed ID: 29743275
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism.
    Tabe-Bordbar S; Marashi SA
    Biotechnol Lett; 2013 Dec; 35(12):2039-44. PubMed ID: 24078125
    [TBL] [Abstract][Full Text] [Related]  

  • 23. gMCS: fast computation of genetic minimal cut sets in large networks.
    Apaolaza I; Valcarcel LV; Planes FJ
    Bioinformatics; 2019 Feb; 35(3):535-537. PubMed ID: 30052768
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Metabolomics integrated elementary flux mode analysis in large metabolic networks.
    Gerstl MP; Ruckerbauer DE; Mattanovich D; Jungreuthmayer C; Zanghellini J
    Sci Rep; 2015 Mar; 5():8930. PubMed ID: 25754258
    [TBL] [Abstract][Full Text] [Related]  

  • 25. regEfmtool: speeding up elementary flux mode calculation using transcriptional regulatory rules in the form of three-state logic.
    Jungreuthmayer C; Ruckerbauer DE; Zanghellini J
    Biosystems; 2013 Jul; 113(1):37-9. PubMed ID: 23664840
    [TBL] [Abstract][Full Text] [Related]  

  • 26. MinReact: a systematic approach for identifying minimal metabolic networks.
    Sambamoorthy G; Raman K
    Bioinformatics; 2020 Aug; 36(15):4309-4315. PubMed ID: 32407533
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks.
    Pratapa A; Balachandran S; Raman K
    Bioinformatics; 2015 Oct; 31(20):3299-305. PubMed ID: 26085504
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models.
    Saa PA; Nielsen LK
    Bioinformatics; 2016 Dec; 32(24):3807-3814. PubMed ID: 27559155
    [TBL] [Abstract][Full Text] [Related]  

  • 29. METATOOL: for studying metabolic networks.
    Pfeiffer T; Sánchez-Valdenebro I; Nuño JC; Montero F; Schuster S
    Bioinformatics; 1999 Mar; 15(3):251-7. PubMed ID: 10222413
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Computing Elementary Flux Modes Involving a Set of Target Reactions.
    David L; Bockmayr A
    IEEE/ACM Trans Comput Biol Bioinform; 2014; 11(6):1099-107. PubMed ID: 26357047
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Algorithmic approaches for computing elementary modes in large biochemical reaction networks.
    Klamt S; Gagneur J; von Kamp A
    Syst Biol (Stevenage); 2005 Dec; 152(4):249-55. PubMed ID: 16986267
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Computing irreversible minimal cut sets in genome-scale metabolic networks via flux cone projection.
    Röhl A; Riou T; Bockmayr A
    Bioinformatics; 2019 Aug; 35(15):2618-2625. PubMed ID: 30590390
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Towards scaling elementary flux mode computation.
    Ullah E; Yosafshahi M; Hassoun S
    Brief Bioinform; 2020 Dec; 21(6):1875-1885. PubMed ID: 31745550
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A depth-first search algorithm to compute elementary flux modes by linear programming.
    Quek LE; Nielsen LK
    BMC Syst Biol; 2014 Jul; 8():94. PubMed ID: 25074068
    [TBL] [Abstract][Full Text] [Related]  

  • 35. al3c: high-performance software for parameter inference using Approximate Bayesian Computation.
    Stram AH; Marjoram P; Chen GK
    Bioinformatics; 2015 Nov; 31(21):3549-51. PubMed ID: 26142186
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A note on the complexity of finding and enumerating elementary modes.
    Acuña V; Marchetti-Spaccamela A; Sagot MF; Stougie L
    Biosystems; 2010 Mar; 99(3):210-4. PubMed ID: 19962421
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Probabilistic thermodynamic analysis of metabolic networks.
    Gollub MG; Kaltenbach HM; Stelling J
    Bioinformatics; 2021 Sep; 37(18):2938-2945. PubMed ID: 33755125
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Computation of elementary modes: a unifying framework and the new binary approach.
    Gagneur J; Klamt S
    BMC Bioinformatics; 2004 Nov; 5():175. PubMed ID: 15527509
    [TBL] [Abstract][Full Text] [Related]  

  • 39. PolyRound: polytope rounding for random sampling in metabolic networks.
    Theorell A; Jadebeck JF; Nöh K; Stelling J
    Bioinformatics; 2022 Jan; 38(2):566-567. PubMed ID: 34329395
    [TBL] [Abstract][Full Text] [Related]  

  • 40. DistributedFBA.jl: high-level, high-performance flux balance analysis in Julia.
    Heirendt L; Thiele I; Fleming RMT
    Bioinformatics; 2017 May; 33(9):1421-1423. PubMed ID: 28453682
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.