For developers and scientists

Run a biology lab. Ship your version.

Pull a published growth lab, fork the model into your own lab, then publish to the Hub. About 30 minutes.

~/growth-lab
$ biosimulant auth login
$ LAB_REF="demi/microbiology-hello-world-growth-lab"
$ biosimulant labs serve "$LAB_REF"
$ biosimulant labs pull "$LAB_REF" --target ./hello-world
$ biosimulant labs init ./growth-lab --name "Growth Lab"
-> wrote ./growth-lab/lab.yaml
$ biosimulant labs add-model ./growth-lab ./hello-world/owned/models/microbial_growth --as microbial_growth
$ biosimulant labs validate ./growth-lab
ok lab is valid
$ biosimulant labs serve ./growth-lab
-> http://127.0.0.1:8765
The build flow

From install to your own published lab

Five steps, one running example. Pull down a published lab, fork its model into your own lab, then publish your version to the Hub.

Step 01

Install the desktop app

Install the desktop app on your laptop. It bundles the visual workbench and the same biosimulant CLI for terminal-first or CI use. You'll need this to pull the published growth lab in step 2.

  • Open Settings > CLI Tools in the desktop app to enable the biosimulant command on your PATH.
  • Use auth login once before publishing or accessing private Hub assets.
setup
# install the desktop app, then open Settings > CLI Tools to add biosimulant to PATH
$ biosimulant doctor
-> CLI installed and data directory detected
$ biosimulant auth login
ok authenticated
Step 02

Reproduce the published growth lab

Pull the published microbiology growth lab and run it locally. You get the exact package, a browser report, and a results file before writing your own version.

  • Exact refs use name@version, so you reproduce the exact same simulation everyone else gets.
  • The CLI pulls or reuses the package under the target folder, then writes results.json and a browser report.
reproduce
$ LAB_REF="demi/microbiology-hello-world-growth-lab"
$ biosimulant labs serve "$LAB_REF"
-> cached the public hello-world lab
ok local SimUI ready at http://127.0.0.1:8765
Step 03

Fork it as a local lab

Initialize your own lab and add the model from the pulled package by path. The CLI copies the model into your lab, so you can edit it without mutating the original package.

  • lab.yaml is the editable unit. Everything in ./growth-lab/owned is yours to change.
  • Models can be added by path, exact package ref, or existing local ID.
fork
$ biosimulant labs init ./growth-lab --name "Growth Lab"
$ biosimulant labs add-model ./growth-lab ./hello-world/owned/models/microbial_growth --as microbial_growth
-> wrote ./growth-lab/lab.yaml
-> copied model into ./growth-lab/owned/models/microbial_growth
# now edit the copied model or tune lab.yaml runtime inputs
Step 04

Validate, serve, inspect the run

Run validation, then open the local browser UI. Adjust inputs, start runs, and inspect status, logs, results, and visuals from the same lab folder.

  • Validation checks the manifest and nested dependency references before you waste a long run.
  • Use --no-open when a server or CI runner should not launch a browser.
~/growth-lab
$ biosimulant labs validate ./growth-lab
-> checking lab.yaml
-> resolving model and child-lab references
ok lab is valid
$ biosimulant labs serve ./growth-lab
-> http://127.0.0.1:8765
Step 05

Run headlessly and publish your version

Lock in a repeatable run, then publish your forked lab to the Hub. Keep it private while you iterate, flip it public when you're ready to share it.

  • Results and reports can be written to stable paths so CI can diff runs across commits.
  • Lab and model publish commands use the same publish language, so promoting your model later works the same way.
~/growth-lab
$ biosimulant labs run ./growth-lab --results-file results.json --report-file run-report.html --json
-> local run completed
$ biosimulant labs publish ./growth-lab --visibility private
ok published to the Hub

Talk to us about your simulation workflow

Biosimulant Platform is for teams building reusable virtual simulations across research and engineering.

  • Research teams building reusable virtual experiments instead of one-off simulations.
  • Simulation groups that need inspectable workflows, reproducible runs, and shared review loops.

Contact

Start the conversation

Tell us what you are simulating, how your team works today, and where Biosimulant might fit.

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