integration_transcriptomics_dynamicmodels
https://github.com/sbcny/integration_transcriptomics_dynamicmodels
Science Score: 57.0%
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○Scientific vocabulary similarity
Low similarity (5.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: SBCNY
- License: other
- Language: MATLAB
- Default Branch: main
- Size: 269 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Arachidonic acid metabolism
The uploaded MATLAB code simulates arachidonic acid metabolism in bone marrow derived macrophages under consideration of initial and time-dependent enzyme expression levels, as predicted from proteomics and transcriptomic datasets. Results of the simulation are part of our manuscript:
Hansen J, Jain AR, Nenov P, Robinson PN and Iyengar R (2024), From transcriptomics to digital twins of organ function. Front. Cell Dev. Biol. 12:1240384. doi: 10.3389/fcell.2024.1240384. PMID: 38989060.
The graphml-file can be opened with yED editor (yworks.com/products/yed) and shows the modeled reactions and their subcellular localizations. The reaction numbers in the yED network correspond to the reaction numbers in the MATLAB code. Network layout is 'organic'.Reactions within the same subcellular compartment are boxed and can be copy pasted into a new file to remove the membrane association/dissociation arrows. Selection of Windows/context views/neighborhood allows visualization of single reactions.
MATLAB code and graphml file were automatically written by an unpublished C# script that integrates canonical dynamical models with transcriptomic and/or proteomic steady state and/or timeline data to generate cell type selective models.
Owner
- Name: Systems Biology Center New York
- Login: SBCNY
- Kind: user
- Location: Icahn School of Medicine at Mount Sinai, New York, NY
- Website: http://sbcny.org/
- Repositories: 3
- Profile: https://github.com/SBCNY
Citation (Citation.cff)
Please cite our manuscript for the generated code:<br> Hansen J, Jain AR, Nenov P, Robinson PN and Iyengar R (2024), From transcriptomics to digital twins of organ function. Front. Cell Dev. Biol. 12:1240384. doi: 10.3389/fcell.2024.1240384.<br> <br>