KAIS Systems — molecular mechanism knowledge graph
KAIS Systems reconstructs signed, directional molecular mechanisms across genes, proteins, metabolites, drugs and diseases — from over 100 million interactions extracted from the published literature. Any claim can be checked in one click.
Stimulation with TNF-α produced a marked increase in IL-6 transcript levels in cultured synovial fibroblasts.
Illustrative records. Every interaction in the knowledge base resolves to this structure — typed nodes, a signed directed relation, and the source text.
Method
Association is cheap. What a reviewer, a regulator or a programme committee needs is direction, evidence, and the ability to get the same answer twice.
We record that A upregulates B, not that A and B are associated. Relations are typed across expression, activity, modification, degradation, transport and binding — each one directed and signed. That distinction is what separates a mechanism from a correlation.
Every edge carries the PMID and the sentence the claim was extracted from, along with organism and cell line. Nothing has to be taken on trust, and nothing has to be traced back through a citation chain by hand.
Knowledge base releases are frozen, dated and versioned. The same query against the same release returns the same result in three years — which is what a regulatory submission requires and what a generative system cannot offer.
Compare
Run the same input through all of them. We would rather you did.
| Capability | KAIS | IPA | MetaCore | STRING |
|---|---|---|---|---|
| Signed, directed relations | Yes | Partial | Partial | No |
| Source sentence per edge | Yes | Citation only | Citation only | Score only |
| Genes and proteins as separate nodes | Yes | No | No | No |
| Tissue-resolved networks | 272 tissues | Limited | Limited | No |
| Path-pattern queries | Yes | No | No | No |
| Custom knowledge base builds | Yes | No | No | No |
| Plant and agricultural coverage | Yes | Limited | Limited | Yes |
| Frozen, versioned releases | Yes | Annual cycle | Annual cycle | Yes |
Work with us
Send us a gene, protein or metabolite list, or a compound and an endpoint. We return the reconstructed networks, hub and tissue analysis, enrichment statistics, and the complete evidence table with every supporting sentence. Four to six weeks, fixed price.
For teams with a deadline and no tooling
A knowledge base built for your compound class, crop, therapeutic area or endpoint set — using the same extraction pipeline, tuned to your domain ontology. Delivered as a versioned release you own and we maintain.
For programmes the general databases do not cover
Run it yourself. Query wizard, network expansion, path-pattern templates, filtering and export, against frozen knowledge base releases. Per seat or site-wide, on our infrastructure or inside your firewall.
For groups doing this work continuously
Record
The method has been applied and peer-reviewed across human disease, agriculture, toxicology and extreme-environment physiology.
Infectious disease
Plasma metabolomics across COVID-19 patients and controls, with networks reconstructing how viral proteins regulate the perturbed pathways. Published in Scientific Reports.
Metabolic disease
Networks linking genes associated with both hyperglycaemia and hypoglycaemia, resolved across pancreatic, cardiovascular, adipose, muscle, renal and gastrointestinal tissue.
Space physiology
Urine and blood proteome analysis following ISS missions of 169 to 199 days, identifying cardiovascular markers linked to inflammation, coagulation and radiation response.
Agriculture and toxicology
A dedicated potato knowledge base spanning genetics, markers, breeding, pathogens and pests — and regulatory pathway reconstruction for chemical toxicity mechanisms.
Start here
The fastest way to evaluate this is on your own data. Send a list of genes, proteins or metabolites and the question you are trying to answer. We will run it and walk you through what came back, with the evidence attached.
Email the team