> For the complete documentation index, see [llms.txt](https://docs.mithrl.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mithrl.com/docs/mithrl-1-inference-engines.md).

# Mithrl-1 Inference Engines

The following are built-in inference algorithms used to navigate the Mithrl Knowledge Graph.

<table><thead><tr><th width="136.8984375">Name</th><th width="375.265625">Short Description</th><th width="440">Scientific Question</th></tr></thead><tbody><tr><td>Pathway Participants</td><td>For one named pathway, list its participants in a chosen ontological category with the provenance of every membership assertion, plus a diagram reference derived from the pathway's CURIE.</td><td>What is actually in the pathway I named — which entities does this build assert participate in it, on whose authority, and where can I see its diagram?</td></tr><tr><td>Compound Tox Profile Card</td><td>For one compound CURIE, list the diseases CTD curators directly associated with it, labelled marker/mechanism or therapeutic, with the citations behind each association.</td><td>Which diseases has CTD directly curated for the compound I named, on which DirectEvidence, and on what published evidence — separately from anything merely inferred through its affected genes?</td></tr><tr><td>Upstream Regulators</td><td>Find the upstream regulators for a set of genes/features.</td><td>Which regulators are most likely driving the supplied expression signature?</td></tr><tr><td>Upstream Regulator Analysis</td><td>Test which upstream regulators are over-represented among the features you measured, against an explicit assayed background, and return each hit with its overlapping targets and citations.</td><td>Given a feature table, which upstream regulators have significantly more of their known targets among my features than the measured background would predict?</td></tr><tr><td>Toxicity Endpoint Analysis</td><td>Test which of the 26 curated toxicity endpoints are over-represented among the features you measured, against an explicit assayed background, with citations on every published endpoint.</td><td>Given a feature table, which curated toxicity endpoints are enriched for my features relative to the measured background — i.e. what toxicity is this signature consistent with?</td></tr><tr><td>Regulator Breakdown</td><td>For the regulators you name, return every asserted regulator-target edge with its predicate, qualifiers, sign and citations — uncapped and unaggregated.</td><td>For the regulators I named, which targets does each act on, by what predicate, with what polarity and on which publications — the per-edge evidence an enrichment result summarises away?</td></tr><tr><td>Pathway Lookup</td><td>List every annotated Reactome pathway the supplied genes participate in, and which genes fall in each — membership only, with no statistical test.</td><td>Which Reactome pathways contain the genes I supplied, and which of my genes are in each, including the pathways an enrichment test would drop for being too small or unremarkable?</td></tr><tr><td>Over-representation</td><td>Test a feature list for over-representation in a supplied term family.</td><td>Which terms are over-represented in this feature list, against an explicit background?</td></tr><tr><td>Compound Tox Profile</td><td>Needs one upload — omics_csv, a feature table whose entity column holds your compounds (rename the column with --param entity_column=&#x3C;name>). Lists the genes each compound is asserted to affect with the sign and citations of every edge, alongside the member genes of the 26 curated toxicity endpoints.</td><td>For the compounds I named, which genes does each one affect and on what evidence, and how do those targets sit against the curated toxicity endpoint gene sets?</td></tr><tr><td>Canonical Pathway Analysis</td><td>Needs TWO uploads — omics_csv (your feature table) and background_csv (the assayed background). Tests which annotated pathways are over-represented among the features you measured against that background, returning each hit with its overlapping members and citations. If you have no background to declare, `pathway-lookup` lists the pathways containing your genes from omics_csv alone, without a statistical test.</td><td>Given a feature table, which canonical pathways contain significantly more of my features than the measured background would predict?</td></tr></tbody></table>
