Data for: 'EnzymeML-based modeling workflow: from raw data to kinetic parameters'
M. Häußler. Dataset, (2024)Related to: Häussler M, Prins A, Le Roes-Hill M, Wittig U, Pleiss, J. (2024) EnzymeML-based modeling workflow: from raw data to kinetic parameters. ChemCatChem.
DOI: 10.18419/darus-3867
Abstract
Kinetic parameter estimates for small laccase (SLAC) catalyzed oxidation of ABTS, investigated across the temperature range between 25 °C and 45°C. This dataset contains the following files:Unprocessed absorption data from the respective enzyme assays (.txt)Derived calibration data for the respective calibration measurements (.json)EnzymeML Documents (.omex) withExperimental conditionsMeasurement dataEstimated parameters and applied modelsAnalysis notebook (.ipynb)Python requirements.txt for all dependencies
Related to: Häussler M, Prins A, Le Roes-Hill M, Wittig U, Pleiss, J. (2024) EnzymeML-based modeling workflow: from raw data to kinetic parameters. ChemCatChem
%0 Generic
%1 haussler2024enzymemlbased
%A Häußler, Max
%D 2024
%K darus ubs_10003 ubs_20003 ubs_30187 ubs_40353 unibibliografie
%R 10.18419/darus-3867
%T Data for: 'EnzymeML-based modeling workflow: from raw data to kinetic parameters'
%X Kinetic parameter estimates for small laccase (SLAC) catalyzed oxidation of ABTS, investigated across the temperature range between 25 °C and 45°C. This dataset contains the following files:Unprocessed absorption data from the respective enzyme assays (.txt)Derived calibration data for the respective calibration measurements (.json)EnzymeML Documents (.omex) withExperimental conditionsMeasurement dataEstimated parameters and applied modelsAnalysis notebook (.ipynb)Python requirements.txt for all dependencies
@misc{haussler2024enzymemlbased,
abstract = {Kinetic parameter estimates for small laccase (SLAC) catalyzed oxidation of ABTS, investigated across the temperature range between 25 °C and 45°C. This dataset contains the following files:Unprocessed absorption data from the respective enzyme assays (.txt)Derived calibration data for the respective calibration measurements (.json)EnzymeML Documents (.omex) withExperimental conditionsMeasurement dataEstimated parameters and applied modelsAnalysis notebook (.ipynb)Python requirements.txt for all dependencies },
added-at = {2024-01-15T12:35:53.000+0100},
affiliation = {Häussler, Max/University of Stuttgart},
author = {Häußler, Max},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/27a7c9cfaa8b709b9aa373564f97c7e23/unibiblio},
doi = {10.18419/darus-3867},
howpublished = {Dataset},
interhash = {ab6852daeb3686cf6efd44be83ca409f},
intrahash = {7a7c9cfaa8b709b9aa373564f97c7e23},
keywords = {darus ubs_10003 ubs_20003 ubs_30187 ubs_40353 unibibliografie},
note = {Related to: Häussler M, Prins A, Le Roes-Hill M, Wittig U, Pleiss, J. (2024) EnzymeML-based modeling workflow: from raw data to kinetic parameters. ChemCatChem},
orcid-numbers = {Häussler, Max/0000-0001-7306-7503},
timestamp = {2024-01-15T12:35:53.000+0100},
title = {Data for: 'EnzymeML-based modeling workflow: from raw data to kinetic parameters'},
year = 2024
}
