"Symbolic kinetic models in python (SKiMpy): intuitive modeling of ..."

Daniel Weilandt et al. (2023)

> Home

Details and statistics

DOI: 10.1093/BIOINFORMATICS/BTAC787

access: open

type: Journal Article

metadata version: 2025-10-28

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/bioinformatics/WeilandtSMFDHH23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/bioinformatics/WeilandtSMFDHH23
Daniel Weilandt, Pierre Salvy, Maria Masid, Georgios Fengos, Robin Denhardt-Erikson, Zhaleh Hosseini, Vassily Hatzimanikatis:
Symbolic kinetic models in python (SKiMpy): intuitive modeling of large-scale biological kinetic models. Bioinform. 39(1) (2023)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.