Assays

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1428 Assays visible to you, out of a total of 2445

Kinetic characterisation en mathematical modelling of TPI.

Kinetic characterisation en mathematical modelling of G3PDH.

Kinetic characterisation en mathematical modelling of GAPDH.

Kinetic characterisation en mathematical modelling of PGK.

Kinetic characterisation en mathematical modelling of PGM.

Kinetic characterisation en mathematical modelling of ENO.

Kinetic characterisation en mathematical modelling of PK.

Kinetic characterisation and mathematical modelling of LDH.

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Submitter: Dawie van Niekerk

Biological problem addressed: Model Analysis Type

Investigation: Glucose metabolism in Plasmodium falciparum tro...

Study: Model validation

RobOKoD algorithm was, designed then implemented as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain. It was shown to perform better than similar methods (OptKnock, and RobustKnock).

OptKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.

RobustKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.

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Time-dependent simulations of the dynamic switch between acidogenesis and solventogenesis based on the metabolic network and pH-dependent regulation of the enzymes.

Steady state study of the effect of altering gene regulation on yields of end-products, focusing on butanol.

Theoretical analysis of hypothetical sigma factor competition. Based on the model 'transcription factor competition' possible dynamics of sigma factor competition are simulated and analysed using Lineweaver-Burk representations.

We use BSA115 strain which lacks RsbU and RsbW proteins. Therefore, there is limited post-transcriptional regulation of sigmaB activity.

There occurs an unexpected drop in the beta-Gal activity after sigB induction. This modelling effort aims to clarify the reasons.

The dynamic model describes response of yeast metabolic network on metabolic perturbation (i.e. glucose-pulse). One compartmental ODE-based model of yeast anaerobic metabolism includes: glycolysis, pentose phosphate reactions, purine de novo synthesis pathway, purine salvage reactions, redox reactions and biomass growth. The model describes metabolic perturbation of steady state growing cells in chemostat.

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  • Comparison of metabolic flux distribution in carbon core metabolism (EMP, PPP, TCA) of Bacillus subtilis under 3 different conditions: "salt-free" reference, "stress" chemostat, "osmoprotected" chemostat.
  • Model created using OpenFLUX and Microsoft Excel
  • Model computed using MatLAB

Using PCA, three components, beam size 8. Clustering via MCL from Biolayout Express 3D

Data is taken from "Genome-Wide Gene Expression Analysis of the Switch between Acidogenesis and Solventogenesis in Continuous Cultures of Clostridium acetobutylicum." Grimmler et al. 2011 DOI: 10.1159/000320973

Pyruvate formate-lyase (PFL) is an important enzyme in the metabolic pathway of lactic acid bacteria (LAB) and is held responsible for the regulation of the shift between homolactic acid to mixed acid fermentation. PFL catalysis the reversible reaction of acetyl-CoA and formate into pyruvate and CoA. A glycyl radical, who is regenerated within the reaction, is involved; therefore, PFL works only under strictly anaerobic conditions. For its activation, the C-terminal domain has to bind to the ...

Submitter: Stefan Henrich

Biological problem addressed: Model Analysis Type

Investigation: The Attic

Study: Pyruvate formate-lyase (PFL)

Metabolic network of S. pyogenes including primary metabolism, polysaccharide metabolism, purine and pyrimidine biosoynthesis, teichoic acid biosynthesis, fatty acid and phospholipid bioynthesis, amino acid metabolism, vitamins and cofactors

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