Linear Fits and Michaelis Menten plot
This is the Jupyter Notebook to allow editing and working with the code.
This Jupyter notebook needs to be located in the same place as a folder "data" and a folder "classes" to run.
"data" must contain the csv with the raw data, see the example data that is provided (MM_25nM_Gre2p_NDK_NADPH_absorbance_340nm_cleaned.csv).
"classes" must contain the file "MMKinetics.py", which is provided here on FAIRDOMhub.
The notebook load the functions from MMKinetics.py and reads in the csv file.
It requires some user input, as explained in the notebook, to run an analysis.
It creates 3 plots in total. Figurelegends to the plot can be edited in "MMKinetics.py".
SEEK ID: https://fairdomhub.org/sops/505?version=1
Filename:
MichaelisMentenNotebook.ipynb
Format: Jupyter notebook document
Size: 4.47 MB
Export PNG
Creators and Submitter
Views: 1171 Downloads: 44
Created: 11th Oct 2021 at 09:57
Last updated: 28th Jan 2022 at 12:44
TagsThis item has not yet been tagged.
AttributionsNone
Version History
Version 2 (latest) Created 28th Jan 2022 at 12:42 by Gudrun Gygli
This rewritten version of the notebook now includes different kinetic models and the option to add more kinetic models. This zip now contains the plots and raw data as well as all the scripts needed by the notebook. Instructions on usage are now included in the notebook.
Version 1 (earliest) Created 11th Oct 2021 at 09:57 by Gudrun Gygli
No revision comments
Related items
https://orcid.org/0000-0001-9119-1778Polyglot European Scientist. I thrive working in interdisciplinary environments combining the study of enzyme reactions and mechanisms with bioinformatics, molecular modelling, automated data analysis and data stewardship.
Work of the Gygli group...
Projects: Test Project (dummy), Towards Reproducible Enzyme Modeling
Web page: Not specified
Investigation 1: An experimental workflow to provide detailed information of the molecular mechanisms of enzymes is described. This workflow will help in the application of enzymes in technical processes by providing crucial parameters needed to plan, model and implement biocatalytic processes more efficiently. These parameters are homogeneity of the enzyme sample (HES), kinetic and thermodynamic parameters of enzyme kinetics and binding of reactants to enzymes. The techniques used to measure ...
Because enzyme activity depends very much on the reaction conditions, it is crucial to report all these metadata (see for example the STRENDA Guidelines:https://www.beilstein-strenda-db.org/strenda/public/guidelines.xhtml).
Another challenge in experiments to determine enzyme reaction parameters is the choice of suitable substrate concentrations to enable optimal kinetic fits and the informed choice of a kinetic model.
A Jupyter notebook is given to assist in the choice of substrate concentrations ...
Submitter: Gudrun Gygli
Studies: Analyse an Initial Rate Experiment, Design an Initial Rate Experiment, Progress Curve Analysis, Selwyn Test
Assays: Use a Jupyter Notebook to design an initital rate experiment, Use a Jupyter Notebook to model Michaelis-Menten Kinetics on experimenta..., Use a Jupyter Notebook to understand how a progress curve experiment can..., Use a Jupyter Notebook to understand how the Selwyn test works
This Jupyter Notebook assists you in the analysis of initial rate experiments.
For help on installing the classical Jupyter Notebook, see here: https://jupyter.org/install
For documentation about Juypter Notebooks, see here: https://jupyter-notebook.readthedocs.io/en/stable/
There are multiple tutorials online that help you to learn how to use a Jupyter notebook.
The notebook is provided as an .ipynb and as a .pdf file. The plots the script generates with the default input data are also given as ...
Submitter: Gudrun Gygli
Biological problem addressed: Model Analysis Type
Investigation: On the reproducibility of enzyme reactions and ...
