BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

117 related articles for article (PubMed ID: 36603705)

  • 1. Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale.
    Hu M; Dinh HV; Shen Y; Suthers PF; Foster CJ; Call CM; Ye X; Pratas J; Fatma Z; Zhao H; Rabinowitz JD; Maranas CD
    Metab Eng; 2023 Mar; 76():1-17. PubMed ID: 36603705
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data.
    Khodayari A; Zomorrodi AR; Liao JC; Maranas CD
    Metab Eng; 2014 Sep; 25():50-62. PubMed ID: 24928774
    [TBL] [Abstract][Full Text] [Related]  

  • 3. From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline.
    Foster CJ; Gopalakrishnan S; Antoniewicz MR; Maranas CD
    PLoS Comput Biol; 2019 Sep; 15(9):e1007319. PubMed ID: 31504032
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Metabolic flux sampling predicts strain-dependent differences related to aroma production among commercial wine yeasts.
    Scott WT; Smid EJ; Block DE; Notebaart RA
    Microb Cell Fact; 2021 Oct; 20(1):204. PubMed ID: 34674718
    [TBL] [Abstract][Full Text] [Related]  

  • 5. k-OptForce: integrating kinetics with flux balance analysis for strain design.
    Chowdhury A; Zomorrodi AR; Maranas CD
    PLoS Comput Biol; 2014 Feb; 10(2):e1003487. PubMed ID: 24586136
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains.
    Khodayari A; Maranas CD
    Nat Commun; 2016 Dec; 7():13806. PubMed ID: 27996047
    [TBL] [Abstract][Full Text] [Related]  

  • 7. De novo sequencing, assembly and analysis of the genome of the laboratory strain Saccharomyces cerevisiae CEN.PK113-7D, a model for modern industrial biotechnology.
    Nijkamp JF; van den Broek M; Datema E; de Kok S; Bosman L; Luttik MA; Daran-Lapujade P; Vongsangnak W; Nielsen J; Heijne WH; Klaassen P; Paddon CJ; Platt D; Kötter P; van Ham RC; Reinders MJ; Pronk JT; de Ridder D; Daran JM
    Microb Cell Fact; 2012 Mar; 11():36. PubMed ID: 22448915
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Genome-Scale
    Ando D; García Martín H
    Methods Mol Biol; 2019; 1859():317-345. PubMed ID: 30421239
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Metabolic analysis of the synthesis of high levels of intracellular human SOD in Saccharomyces cerevisiae rhSOD 2060 411 SGA122.
    Gonzalez R; Andrews BA; Molitor J; Asenjo JA
    Biotechnol Bioeng; 2003 Apr; 82(2):152-69. PubMed ID: 12584757
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluation of rate law approximations in bottom-up kinetic models of metabolism.
    Du B; Zielinski DC; Kavvas ES; Dräger A; Tan J; Zhang Z; Ruggiero KE; Arzumanyan GA; Palsson BO
    BMC Syst Biol; 2016 Jun; 10(1):40. PubMed ID: 27266508
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Comparative genotyping of the Saccharomyces cerevisiae laboratory strains S288C and CEN.PK113-7D using oligonucleotide microarrays.
    Daran-Lapujade P; Daran JM; Kötter P; Petit T; Piper MD; Pronk JT
    FEMS Yeast Res; 2003 Dec; 4(3):259-69. PubMed ID: 14654430
    [TBL] [Abstract][Full Text] [Related]  

  • 12. K-FIT: An accelerated kinetic parameterization algorithm using steady-state fluxomic data.
    Gopalakrishnan S; Dash S; Maranas C
    Metab Eng; 2020 Sep; 61():197-205. PubMed ID: 32173504
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Benchmarking two
    Espinosa MI; Williams TC; Pretorius IS; Paulsen IT
    Synth Syst Biotechnol; 2019 Dec; 4(4):180-188. PubMed ID: 31667368
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Catabolite repression mutants of Saccharomyces cerevisiae show altered fermentative metabolism as well as cell cycle behavior in glucose-limited chemostat cultures.
    Aon MA; Cortassa S
    Biotechnol Bioeng; 1998 Jul; 59(2):203-13. PubMed ID: 10099331
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Continuous modeling of metabolic networks with gene regulation in yeast and in vivo determination of rate parameters.
    Moisset P; Vaisman D; Cintolesi A; Urrutia J; Rapaport I; Andrews BA; Asenjo JA
    Biotechnol Bioeng; 2012 Sep; 109(9):2325-39. PubMed ID: 22447363
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Comparative
    Yatabe F; Okahashi N; Seike T; Matsuda F
    Biotechnol J; 2022 Mar; 17(3):e2000438. PubMed ID: 33983677
    [TBL] [Abstract][Full Text] [Related]  

  • 17. In vivo dynamics of galactose metabolism in Saccharomyces cerevisiae: metabolic fluxes and metabolite levels.
    Ostergaard S; Olsson L; Nielsen J
    Biotechnol Bioeng; 2001 Jun; 73(5):412-25. PubMed ID: 11320512
    [TBL] [Abstract][Full Text] [Related]  

  • 18. E-Flux2 and SPOT: Validated Methods for Inferring Intracellular Metabolic Flux Distributions from Transcriptomic Data.
    Kim MK; Lane A; Kelley JJ; Lun DS
    PLoS One; 2016; 11(6):e0157101. PubMed ID: 27327084
    [TBL] [Abstract][Full Text] [Related]  

  • 19. (13)C-metabolic flux analysis in S-adenosyl-L-methionine production by Saccharomyces cerevisiae.
    Hayakawa K; Kajihata S; Matsuda F; Shimizu H
    J Biosci Bioeng; 2015 Nov; 120(5):532-8. PubMed ID: 25912448
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A method for analysis and design of metabolism using metabolomics data and kinetic models: Application on lipidomics using a novel kinetic model of sphingolipid metabolism.
    Savoglidis G; da Silveira Dos Santos AX; Riezman I; Angelino P; Riezman H; Hatzimanikatis V
    Metab Eng; 2016 Sep; 37():46-62. PubMed ID: 27113440
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.