Open-source biomedical research software
NosoGraph
Disease Intelligence. Connected.
Open-source research software for connecting disease knowledge, evidence, and provenance across biomedical sources.
PUBLIC_ALPHA · RESEARCH USE ONLY · NO HOSTED DEMO YET
Select a labeled entity to trace relationships.
Choose a way in
Start with the question you need to answer.
Trace what the graph says—and why.
Explore disease knowledge, inspect claims, review supporting or contradictory evidence, and follow provenance to the source.
For developersInspect the model. Extend the system.
Run the platform locally, inspect the API and data model, add a source or disease, validate it, and contribute the change.
The problem
Biomedical evidence is connected in the literature, but scattered in practice.
Diseases, phenotypes, genes, pathways, trials, publications, and therapies live across different resources. Finding a relationship is only the beginning; researchers also need its context and lineage.
- Distributed knowledge Ontologies, genetics resources, pathway databases, trials, and literature each expose a partial view.
- Hard-to-trace claims A result without its underlying evidence is difficult to review or reproduce.
- Uneven coverage A registry entry is not the same thing as a deeply curated disease module.
- Uncertain context Species, study design, origin, and missing metadata change how evidence should be read.
The NosoGraph layer
Turn fragmented sources into inspectable relationships.
NosoGraph is a computational layer across upstream resources—not a replacement for them. It normalizes records, creates typed claims, attaches evidence, and preserves provenance for downstream inspection.
Evidence-first by design
See why information is present—not only what was generated.
Evidence records support claims; they are not automatic proof. Associations are not causation. Conflicting evidence can coexist, and unknown metadata remains unknown rather than becoming a confident score.
Read the Evidence Explorer guide- Disease context
- Typed claim
- Supporting / contradictory evidence
- Study and source metadata
- Provenance and snapshot
The Evidence Explorer is a read-only public-alpha surface. Quality dimensions such as species, study design, origin, and human review describe context; sparse metadata is shown as unknown.
Real paths, not dead-end cards
From disease question to inspectable evidence.
- Explore a disease and its connected entities
- Inspect claims and evidence directions
- Trace provenance to source snapshots
- Compare relationships with explicit missingness
From architecture to contribution.
- Understand the disease and biomedical store model
- Run the CLI, API, dashboard, and tests locally
- Extend a source adapter or disease module
- Validate the change and open a contribution
What exists today—and what does not.
Maturity labels are part of the product. They tell you how to interpret a surface before you use it.
| Capability | Current state | What that means |
|---|---|---|
Unified nosograph CLI | Stable | Task-oriented commands for exploration, validation, sources, analysis, and serving. |
| FastAPI API + dashboard | Beta | Working local research interface with async jobs and documented API surfaces. |
| Evidence Explorer | Public alpha · included in v0.1.0 | Read-only claim → evidence → provenance → source workflow. |
| Evidence Workspace | Beta | Multi-source evidence assembled into claims and ranked hypotheses. |
| NosoGraph Compare | Experimental | Initial multidimensional comparison with explicit missingness. |
| Public hosted demo | Planned | Not deployed; local Docker evaluation is the current route. |
| Optional LLM enrichment | Experimental | Not required for core deterministic extraction and evidence workflows. |
| FHIR / OMOP / Phenopackets | Not implemented | Future interoperability work, not current capability. |
Snapshot source: public-status.yaml. Registry breadth is not curation depth; most registry modules are scaffolds.
Scientific and technical practice
Trust comes from inspectability.
Source transparency
Upstream resources, integration state, and data terms are documented in a source matrix.
Provenance
Source snapshots, import paths, filters, fingerprints, and retrieval context can travel with an output.
Conservative quality
Species, study design, origin, and human review are contextual dimensions; missing values stay unknown.
Reproducibility
CLI validation, fixture-backed workflows, tests, and explicit maturity make limits visible.
Go deeper
Documentation organized around how you work.
Get started
Understand the model, install locally, and run a first workflow.
Learn the concepts
Evidence, claims, provenance, knowledge graphs, and curation tiers.
Use NosoGraph
Web interface, Evidence Explorer, CLI, API, validation, and source sync.
Inspect the data
Sources, coverage, licensing, provenance, and update cadence.
Build with it
Architecture, data model, local development, testing, and deployment.
See what is next
Read the public roadmap and current release record without inflated promises.
Open implementation · open questions
Read the code. Improve the model.
Add a source, deepen a disease module, improve the evidence workflow, or ask a research question. NosoGraph is built in public and labeled honestly.