<%* const TYPE = "model"; // template note type const title = tp.file.title; const today = tp.date.now("YYYY-MM-DD"); const prefixMap = { gene:"GENE", protein:"PROT", complex:"COMPLEX", ligand:"LIGAND", receptor:"RTK", pathway:"PATHWAY", process:"GO", phenotype:"PHENO", disease:"DISEASE", drug:"DRUG", method:"METHOD", dataset:"DATASET", model:"MODEL", study:"STUDY", concept:"CONCEPT", overview:"OVERVIEW" }; const pref = prefixMap[TYPE] ?? "NODE"; const makeCurie = t => `${pref}:${(t || "").replace(/[^A-Za-z0-9]+/g,"_").replace(/^_|_$/g,"").toUpperCase() || "NAME"}`; let id = makeCurie(title); id = await tp.system.prompt("ID (CURIE)", id); const curator = await tp.system.prompt("Curator initials", "sam"); -%> --- schema: version: 0.3 profile: "onco-entity+learning" curator: "<% curator %>" type: model id: "<% id %>" title: "<% tp.file.title %>" aliases: [] summary: "One-sentence, ≤200 chars." # Cross-cutting facets disease_context: [] # e.g., [dsrct, ewing, pan-cancer] model_system: [] # e.g., [cell_line, clinical, PDX] evidence_strength: Unknown # Strong | Moderate | Weak | Unknown evidence_type: [] # e.g., [in_vitro, in_vivo, clinical, computational] data_type: [] # e.g., [RNA-seq, ChIP-seq, ATAC-seq, WES, IHC, flow] compartment: null # e.g., membrane | cytosol | nucleus | ECM | secreted hallmarks: [] # e.g., [proliferative_signaling, metabolism] confidence: 3 # 1–5 curation_status: draft # Links/IDs links: uniprot: null ncbi_gene: null ensembl: null reactome: null mondo: null doid: null pmid: [] doi: [] # Relations (edges in your graph) # Allowed predicates: activates | inhibits | upregulates | downregulates | binds | phosphorylates | demethylates | # recruits | interacts_with | part_of | involved_in | expressed_in | essential_for | # synthetic_lethal_with | implicated_in relations: - predicate: activates target: "PATHWAY:PI3K_AKT" evidence: [] confidence: 3 # Type-specific pack pack: model: species: "human|mouse" name: "" lineage: "" driver_or_fusion: "" baseline_signals: [] provider: "" # Learning (optional: for card generation) learning: prompt: "" answer: "" difficulty: 2 target_latency_sec: 20 objective_metric: "≤20s, ≥85% accuracy (last 5)" _notes: | Use this for free-form rationale or TODOs. --- # <% tp.file.title %> ## Overview Short paragraph introducing the entity and its role. ## Key Mechanisms / Functions - Point 1 - Point 2 - Point 3 ## Evidence Summary - Study or dataset → finding → relevance (PMID/DOI) - Strength/limitations ## Therapeutic / Clinical Relevance (if applicable) - Targets, biomarkers, resistance routes ## Graph & Relations (internal links) List important edges and link to their pages. ## Figures / Tables (optional) - Insert images or schematics ## Sources - PMID/DOI list kept concise ## Related Topics - [[PI3K–AKT]] · [[RAS–MAPK]] · [[mTOR]] (example links) ## Tags `#type/model` `#theme/tbd` `#disease/tbd` ## Last Updated <% today %>