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stoivia

Metabolic modelling, with context

See the model.
Explore what’s
possible.

A connected workspace for metabolic modelling. Inspect your model, compare constrained scenarios, and keep every result connected to its assumptions.

Built for researchers.
Ready for your next question.

+ Connected by curiosity
A world of pathways.
A clearer way through.
Conceptual cellular artwork

From question to context

Inspect the modelExplore scenariosPreserve the evidence

A connected perspective

Complex systems.
Clearer questions.

See the network without losing the details. Bring model inspection, constrained simulations and the context behind each result into one considered workspace.

Inside the workspaceA guided preview
A connected reconstruction
Every reaction has context

Illustrative network · Not a computed result

The starting point

A. baylyi ADP1

Bundled research reconstruction

durot2008-v1
Reactions
996
Metabolites
828
Genes
774

Research pilot. Chemical curation and independent biological validation remain open.

Know your starting point.

Explore your workspace

Designed around your research

Less scattered work.
More scientific context.

01

Start with the model.

Bring your SBML or JSON reconstruction into one workspace. Inspect reactions, review model quality, and understand the starting point before asking what comes next.

02

Make room for “what if”.

Explore FBA, pFBA, FVA, gene essentiality and knockout scenarios. Keep your objective, medium and exchange bounds explicit as you compare possibilities.

03

Keep the reasoning.

Save the model context, conditions and results together. Return to your assumptions, compare runs, and export a traceable record for scientific review.

Clarity is part of the science

A result is only as useful as
the context you keep with it.

Good models make their assumptions visible. Stoivia helps you hold onto the model, the question and the conditions—so your scientific judgment stays at the centre.

Let’s discuss your study
A record, not just a result

Leave a trace.
Build understanding.

01 The model
Version & source
02 The question
Objective & constraints
03 The result
Saved assumptions & evidence

Experimental validation remains essential.

Before you begin

Good questions.
Honest answers.

Something specific on your mind?
Let’s talk about your research

What can I do in the research pilot?

The pilot supports model inspection, flux balance analysis (FBA), parsimonious FBA, flux variability analysis, gene essentiality and knockout analysis. Advanced experimental methods are outside the pilot scope; 13C-MFA is pending a validated implementation.

Can I work with my own metabolic models?

Yes. You can import supported SBML or JSON models and review their structure and quality. A model still needs an appropriate objective, reaction bounds and experimental context before its predictions can be interpreted.

How should I interpret the predictions?

A prediction describes what is possible within a model and its chosen constraints. It is a hypothesis for scientific review, not proof of biological behaviour. Chemical curation and independent biological validation remain necessary for the bundled ADP1 pilot model.

Where does AI fit into the workflow?

AI assistance is optional and depends on a configured provider. Numerical simulations use the modelling engine and your explicit constraints. AI-generated explanations do not replace the calculations, model curation or scientific judgment.

Your next question starts here

Follow your curiosity.
Keep the evidence.

Start your workspace Metabolic modelling. Thoughtfully connected.