--- title: "Disease Research: Complete Tool Usage by Section" task: "" lineage_type: import upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/e2520a96/skills/tooluniverse-disease-research/tool_usage_details.md upstream_sha: e2520a96 imported_at: 2026-06-26 prompt_class: prompt upstream_changes: accepted author: upstream validated: false --- # Disease Research: Complete Tool Usage by Section Detailed tool calls for each of the 10 research dimensions. --- ## Section 1: Identity (use ALL) ```python tu.tools.OSL_get_efo_id_by_disease_name(disease=disease_name) tu.tools.OpenTargets_get_disease_id_description_by_name(diseaseName=disease_name) tu.tools.ols_search_efo_terms(query=disease_name) tu.tools.ols_get_efo_term(obo_id=efo_id) tu.tools.ols_get_efo_term_children(obo_id=efo_id, size=30) tu.tools.umls_search_concepts(query=disease_name) tu.tools.umls_get_concept_details(cui=cui) tu.tools.icd_search_codes(query=disease_name, version="ICD10CM") tu.tools.snomed_search_concepts(query=disease_name) ``` --- ## Section 2: Clinical Presentation (use ALL) ```python tu.tools.OpenTargets_get_associated_phenotypes_by_disease_efoId(efoId=efo_id) tu.tools.get_HPO_ID_by_phenotype(query=symptom) # for each key symptom tu.tools.get_phenotype_by_HPO_ID(id=hpo_id) # for top phenotypes tu.tools.MedlinePlus_search_topics_by_keyword(term=disease_name, db="healthTopics") tu.tools.MedlinePlus_get_genetics_condition_by_name(condition=disease_slug) tu.tools.MedlinePlus_connect_lookup_by_code(cs=icd_oid, c=icd_code) ``` --- ## Section 3: Genetics (use ALL) ```python tu.tools.OpenTargets_get_associated_targets_by_disease_efoId(efoId=efo_id) tu.tools.OpenTargets_target_disease_evidence(efoId=efo_id, ensemblId=gene_id) # top genes tu.tools.ClinVar_search_variants(condition=disease_name, max_results=50) tu.tools.ClinVar_get_variant_details(variant_id=vid) # top variants tu.tools.ClinVar_get_clinical_significance(variant_id=vid) tu.tools.gwas_search_associations(disease_trait=disease_name, size=50) tu.tools.gwas_get_variants_for_trait(disease_trait=disease_name, size=50) tu.tools.gwas_get_associations_for_trait(disease_trait=disease_name, size=50) tu.tools.gwas_get_studies_for_trait(disease_trait=disease_name, size=30) tu.tools.GWAS_search_associations_by_gene(gene_name=gene) # top genes tu.tools.gnomad_get_variant_frequency(variant=variant) # key variants ``` --- ## Section 4: Treatment (use ALL) ```python tu.tools.OpenTargets_get_associated_drugs_by_disease_efoId(efoId=efo_id, size=100) tu.tools.OpenTargets_get_drug_chembId_by_generic_name(drugName=drug) tu.tools.OpenTargets_get_drug_mechanisms_of_action_by_chemblId(chemblId=chembl_id) tu.tools.search_clinical_trials(condition=disease_name, pageSize=50) tu.tools.get_clinical_trial_descriptions(nct_ids=nct_list) tu.tools.get_clinical_trial_conditions_and_interventions(nct_ids=nct_list) tu.tools.get_clinical_trial_eligibility_criteria(nct_ids=nct_list) tu.tools.get_clinical_trial_outcome_measures(nct_ids=nct_list) tu.tools.extract_clinical_trial_outcomes(nct_ids=nct_list) tu.tools.GtoPdb_search_diseases(name=disease_name) tu.tools.GtoPdb_search_diseases(disease_id=gtopdb_id) ``` --- ## Section 5: Pathways (use ALL) ```python tu.tools.Reactome_get_diseases() tu.tools.Reactome_map_uniprot_to_pathways(uniprot_id=uniprot_id) # top genes tu.tools.Reactome_get_pathway(stId=pathway_id) tu.tools.Reactome_get_pathway_reactions(stId=pathway_id) tu.tools.humanbase_ppi_analysis(gene_list=top_genes, tissue=relevant_tissue) tu.tools.GTEx_get_expression_summary(gene_symbol=gene) # top genes tu.tools.HPA_get_rna_expression_by_source(gene_name=gene) tu.tools.geo_search_datasets(query=disease_name) ``` --- ## Section 6: Literature (use ALL) ```python tu.tools.PubMed_search_articles(query=f'"{disease_name}"', limit=100) tu.tools.PubMed_search_articles(query=f'"{disease_name}" AND epidemiology', limit=50) tu.tools.PubMed_search_articles(query=f'"{disease_name}" AND mechanism', limit=50) tu.tools.PubMed_search_articles(query=f'"{disease_name}" AND treatment', limit=50) tu.tools.PubMed_get_article(pmid=pmid) # top 10 articles tu.tools.PubMed_get_related(pmid=key_pmid) tu.tools.PubMed_get_cited_by(pmid=key_pmid) tu.tools.OpenTargets_get_publications_by_disease_efoId(efoId=efo_id) tu.tools.openalex_search_works(query=disease_name, limit=50) tu.tools.EuropePMC_search_articles(query=disease_name, limit=50) tu.tools.SemanticScholar_search_papers(query=disease_name, limit=50) ``` --- ## Section 7: Similar Diseases ```python tu.tools.OpenTargets_get_similar_entities_by_disease_efoId(efoId=efo_id, threshold=0.3, size=30) ``` --- ## Section 8: Cancer-Specific (if cancer) ```python tu.tools.civic_search_diseases(limit=100) tu.tools.civic_search_genes(query=gene, limit=20) tu.tools.civic_get_variants_by_gene(gene_id=civic_gene_id, limit=50) tu.tools.civic_get_variant(variant_id=vid) tu.tools.civic_get_evidence_item(evidence_id=eid) tu.tools.civic_search_therapies(limit=100) tu.tools.civic_search_molecular_profiles(limit=50) ``` --- ## Section 9: Pharmacology ```python tu.tools.GtoPdb_search_targets(target_type=type, limit=50) # GPCR, ion channel, etc tu.tools.GtoPdb_search_targets(target_id=tid) tu.tools.GtoPdb_get_interactions(target_id=tid) tu.tools.GtoPdb_get_interactions(approved_only=True) tu.tools.GtoPdb_list_ligands(ligand_type="Approved") ``` --- ## Section 10: Safety (use ALL) ```python tu.tools.OpenTargets_get_drug_warnings_by_chemblId(chemblId=cid) tu.tools.OpenTargets_get_drug_blackbox_status_by_chembl_ID(chemblId=cid) tu.tools.extract_clinical_trial_adverse_events(nct_ids=nct_list) tu.tools.FAERS_count_reactions_by_drug_event(drug=drug_name, event=event) tu.tools.AdverseEventPredictionQuestionGenerator(disease_name=disease, drug_name=drug) ``` --- ## Research Protocol ### Step 1: Initialize Report ```python from datetime import datetime filename = f"{disease_name.lower().replace(' ', '_')}_research_report.md" # Write template with placeholders for each section ``` ### Step 2: Research Each Dimension For EACH piece of information, track: - **Tool name** that provided the data - **Parameters** used in the query - **Timestamp** of the query ### Step 3: Update Report After Each Dimension ```python # Read current file # Replace placeholder with formatted content # Write back immediately # Continue to next dimension ```