Data files

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3939 Data files visible to you, out of a total of 5920

Results of the statistical analysis, identifying proteins that change in abundance significantly across photoperiods.

Proteomics data for N15 incorporation into protein in Ostreococcus grown in 12L:12D light:dark cycles.

Quantitative proteomic analysis of Cyanothece ATCC51142 grown in 12L:12D light:dark cycles, using partial metabolic labeling and LC-MS analysis.

Growth curves of the PA1008 strain of Pseudomonas aeruginosa with multiple concentrations of meropenem. Data set 1 is used to parametrise the model in our project. This consists of three biological replicates, each with three technical repeats. The meropenem concentrations used for this data set were: 0, 2, 4, 10, 20, 40, 200 ug/ml.

Growth curves of the PA1008 strain of Pseudomonas aeruginosa with multiple concentrations of meropenem. Data set 1 is used to parametrise the model in our project. This consists of three biological replicates, each with three technical repeats. The meropenem concentrations used for this data set were: 0, 0.5, 1, 5, 10, 50, 100 ug/ml.

No description specified
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Combined taxonomy table of abundance of OTUs (Operational Taxonomy Units) in both freshwater and saltwater samples from 16S V3-V4 Illumina sequencing of gut microbiota. Primers used for sequencing are given in https://fairdomhub.org/sops/270 The OTUs are presented in number of counts per sample (n=349). Each row represent one sample. Raw data are available in the Sequence Read Archive database under accession number SRP119730 (https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP119730).

Agenda for the satellite data management tutorial of Synthetic Biology 2017.

Creator: Natalie Stanford

Submitter: Natalie Stanford

No description specified

Creator: Ulrike Wittig

Submitter: Ulrike Wittig

No description specified

Creator: Ulrike Wittig

Submitter: Ulrike Wittig

No description specified

Creator: Ulrike Wittig

Submitter: Ulrike Wittig

L. lactis cultures were grown at different dilution rates in glucose-limited chemostat conditions and were analyzed with respect to physiological parameters. Amino acid consumption, glucose consumption and production of fermentation products were measured in steady-state conditions,

Creator: Martijn Bekker

Submitter: Martijn Bekker

All datapoints that were measured are displayed together with the accompanying simulations by the computational model

Simulation results of TPI experimental data for GAP and DHAP saturation.

Simulation results of temperature degradation of gluconeogenic intermediates

Simulation results of experimental data of the reconstituted gluconeogenic system

Output of the 3D-structures modeled by comparative modeling tool for LDH enzymes from four LABs (in the PDB format, tarred). Four LABs include Enterococcus faecalis, Lactococcus lactis, Streptococcus pyogenes and Lactobacillus plantarum. Output of the SEEK Model https://seek.sysmo-db.org/models/118.

The modeling was performed against a x-ray structure of LDH from B. stearothermophilis (template, PDH ID: 1LDN).

Output files of phosphate probe binding on the surface of LDH from lactococcus lactis type 1. File with extension XPLOR can be visualized with a program VMD to identify the most favorable position for the phosphate binding. This relates to the Model "Part 4".

The Table represents the simulation results of how the presence of phosphate ions (Pi) in the solution might affect the activity of four LDH enzymes. This includes the algorithmic analysis of the binding energies values computed by the GRID program (see Part 4, model) for each enzyme in presence and absence of FBP molecule at pH 6 and 7. The analysis was performed by using the algorithm proposed in Part 5, model.

The file contains simulated data of the electron transport chain model (EcoliETC1) for varying parameter values, i.e. a local sensitivity analysis.

Excel sheet contains:

  • flux distribution solution from best iteration cluster
  • quality of the fit (experimental MIDs vs. simulated MIDs)
  • Sensitivity analysis for 95% flux parameter confidence interval using a Monte-Carlo approach

Excel sheet contains:

  • flux distribution solution from best iteration cluster
  • quality of the fit (experimental MIDs vs. simulated MIDs)
  • Sensitivity analysis for 95% flux parameter confidence interval using a Monte-Carlo approach

Excel sheet contains:

  • flux distribution solution from best iteration cluster
  • quality of the fit (experimental MIDs vs. simulated MIDs)
  • Sensitivity analysis for 95% flux parameter confidence interval using a Monte-Carlo approach
No description specified
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