BioBTree

Curated Sugi Atlas knowledge for genes, diseases, and drugs (built from biobtree's own data).

SYNTAX: biobtree_atlas(entities=["TP53","imatinib"])

CALL THIS FIRST for a gene/disease/drug question (what it is, its biology, disease/drug/clinical context) - returns a concise, citable digest to ground your answer. Cite the returned canonical_url.

• Pass the entity name(s) from the question; covered entities return content + citation, uncovered ones are listed in not_covered.

• Default returns a compact digest (Summary + Identifiers). Each result lists the page's sections (top-level and sub-sections); pass section="Disease & clinical" (use a name from sections) for one zone, or full=true for the entire page (large). For big sections, query one entity at a time; full=true and large sections across several entities may be trimmed to fit.

• For entities not covered, or for specific ID mappings / cross-references / filters, use biobtree_map / biobtree_entry instead.

RETURNS: per entity {type, canonical_url, content, sections} + not_covered list

Get full details for one identifier.

SYNTAX: biobtree_entry(identifier="ID", dataset="dataset_name")

USE FOR:

• See all attributes of an entry

• Discover filterable fields

• Get detailed info (sequences, scores, descriptions)

• DISCOVER CONNECTIONS: xrefs show what datasets link to this entry

WORKFLOW: Get entry → see xrefs → check EDGES for where they lead → follow relevant paths

RETURNS: All attributes + xref counts to connected datasets

Map identifiers between databases.

SYNTAX: biobtree_map(terms="ID", chain=">>source>>target")

• Chain MUST start with ">>"

• Source MUST match input ID type

ID TYPE → SOURCE:

• ENSG* → >>ensembl

• P*/Q*/O* → >>uniprot

• CHEMBL* → >>chembl_molecule

• GO:* → >>go

• MONDO:* → >>mondo

• HP:* → >>hpo

• HGNC:* or gene symbols → >>hgnc

SOME DRUG EXPLORATION PATHS:

• chembl_molecule>>chembl_target>>uniprot (drug targets)

• pubchem>>pubchem_activity>>uniprot (bioactivity)

• gtopdb_ligand>>gtopdb_interaction>>gtopdb>>uniprot (curated pharmacology with affinity data)

• ensembl>>reactome>>chebi (pathway chemicals - when no direct targets)

• Discover more via entry xrefs + EDGES

WARNING - GO terms with high xref_count (>100):

• Don't map GO → proteins → drugs (too many results)

• Instead: search drug class for condition → verify targets this GO term

DISEASE GENE PATTERNS:

• mondo>>gencc>>hgnc (curated)

• mondo>>clinvar>>hgnc (variant-based)

• hgnc>>clingen_gene_validity (ClinGen evidence tier), >>hgnc>>clingen_dosage (haploinsufficiency), >>hgnc>>clingen_variant>>clinvar (ACMG, then dbsnp)

CANCER / CELL LINE:

• hgnc>>intogen (cancer driver gene?), >>hgnc>>civic (clinical variant interpretations)

• uniprot>>cellosaurus (cell lines for a protein/gene)

• hgnc>>depmap (CRISPR essentiality / target tractability), >>hgnc>>entrez>>depmap_dependency>>cellosaurus (which lines depend on the gene)

GENE FUNCTION / LITERATURE:

• entrez>>generif (cited one-line functional claims; >>generif>>pubmed for citations)

DISEASE → DRUG PATTERNS:

• mesh>>chembl_molecule (MeSH disease/condition → drugs with indications)

• mondo>>clinical_trials>>chembl_molecule (disease → trial drugs)

DISCOVERY APPROACH:

• Use biobtree_entry to see xrefs (what's connected)

• Use EDGES above to see where each dataset leads

• Build chains based on what connections exist for YOUR entity

RETURNS: mapped identifiers with dataset and name

EDGES (what connects to what): ensembl: uniprot, go, transcript, exon, ortholog, paralog, hgnc, entrez, refseq, bgee, gwas, gencc, antibody, scxa, civic, intogen, hpa, hpa_antibody, pharmgkb_var_annotation, chembl_mechanism, ncrna_disease, ncrna_interaction, ncrna_drug, alliance_disease hgnc: ensembl, uniprot, entrez, gencc, pharmgkb_gene, msigdb, clinvar, mim, refseq, alphafold, collectri, gwas, hpo, cellphonedb, civic, intogen, cellosaurus, clingen_gene_validity, clingen_dosage, clingen_variant, depmap, hpa, pharmgkb_var_annotation, chembl_mechanism, ncrna_disease, ncrna_interaction, ncrna_drug, alliance_disease entrez: ensembl, uniprot, refseq, go, biogrid, pubchem_activity, ctd_gene_interaction, dbsnp, civic, intogen, clingen_dosage, generif, depmap, depmap_dependency, hpa, pharmgkb_var_annotation refseq: ensembl, entrez, taxonomy, ccds, uniprot, mirdb mirdb: refseq transcript: ensembl, exon, ufeature, alphamissense uniprot: ensembl, alphafold, interpro, pfam, pdb, ufeature, intact, string, string_interaction, biogrid, biogrid_interaction, chembl_target, go, reactome, rhea, swisslipids, bindingdb, antibody, pubchem_activity, cellphonedb, jaspar, signor, diamond_similarity, esm2_similarity, alphamissense, cellosaurus, hpa, chembl_mechanism, ncrna_interaction alphafold: uniprot interpro: uniprot, go, interproparent, interprochild chembl_molecule: mesh, chembl_activity, chembl_target, pubchem, chebi, clinical_trials, chembl_moleculeparent, chembl_moleculechild, chembl_mechanism, ncrna_drug # parent=anhydrous/parent form, child=salt forms chembl_activity: chembl_molecule, chembl_assay, bao chembl_assay: chembl_activity, chembl_target, chembl_document, bao chembl_target: chembl_assay, uniprot, chembl_molecule, chembl_mechanism chembl_mechanism: chembl_molecule, chembl_target, uniprot, hgnc, ensembl # curated drug mechanism-of-action (incl. RNA therapeutics): drug >> chembl_mechanism, target/gene >> chembl_mechanism pubchem: chembl_molecule, chebi, hmdb, pubchem_activity, pubmed, patent_compound, bindingdb, ctd, pharmgkb, ncrna_drug pubchem_activity: pubchem, ensembl, uniprot chebi: pubchem, rhea, intact swisslipids: uniprot, go, chebi, uberon, cl lipidmaps: chebi, pubchem dbsnp: entrez, clinvar, pharmgkb_variant, alphamissense, spliceai, pharmgkb_var_annotation clinvar: hgnc, mondo, hpo, dbsnp, orphanet, civic_variant, cellosaurus, clingen_variant alphamissense: uniprot, transcript gwas: gwas_study, efo, dbsnp, hgnc, mondo gwas_study: gwas, efo, mondo mondo: gencc, clinvar, efo, mesh, hpo, clinical_trials, antibody, cellxgene, cellxgene_celltype, orphanet, mondoparent, mondochild, gwas, gwas_study, civic, intogen, cellosaurus, doid, mim, ncit, umls, medgen, gard, sctid, icd9, icd10cm, icd10who, icd11, nando, meddra, nord, uberon, ncrna_disease # disease cross-refs + disease_has_location anatomy, from the Mondo OBO doid: mondo, alliance_disease, doidparent, doidchild # Disease Ontology (now a full ontology w/ hierarchy); reach MONDO + its disease graph via the mondo<->doid bridge alliance_disease: hgnc, mgi, rgd, zfin, sgd, wormbase, flybase, xenbase, doid, pubmed # cross-species + human gene->disease (Alliance of Genome Resources); gene >> alliance_disease >> doid, or doid >> alliance_disease >> mgi/rgd/... for model-organism genes gencc: mondo, hpo, hgnc, ensembl clingen_gene_validity: hgnc, entrez, ensembl, mondo # ClinGen gene-disease validity tier (Definitive..Refuted) + MOI clingen_dosage: entrez, hgnc, ensembl, mondo, mim, pubmed # ClinGen haploinsufficiency/triplosensitivity per gene clingen_variant: clinvar, hgnc, entrez, ensembl, mondo, pubmed # ClinGen VCEP ACMG variant pathogenicity (clinvar bridges to dbsnp) clinical_trials: mondo, chembl_molecule pharmgkb: hgnc, dbsnp, mesh, pharmgkb_gene, pharmgkb_variant, pharmgkb_clinical, pharmgkb_guideline, pharmgkb_pathway pharmgkb_variant: pharmgkb_clinical, hgnc, mesh, dbsnp pharmgkb_gene: hgnc, entrez, ensembl, pharmgkb pharmgkb_clinical: dbsnp, hgnc, mesh, pharmgkb_variant, pharmgkb # pharmgkb = reverse drug→clinical edge (drug >> pharmgkb >> pharmgkb_clinical) pharmgkb_guideline: hgnc, pharmgkb pharmgkb_pathway: hgnc, pharmgkb pharmgkb_var_annotation: hgnc, entrez, ensembl, dbsnp, pubmed # per-publication variant-annotation evidence (finding sentence, PMID, significance, study stats) beneath pharmgkb_clinical; reach via gene or rsID ctd: mesh, ctd_gene_interaction, ctd_disease_association, pubchem ctd_gene_interaction: ctd, entrez, taxonomy, pubmed ctd_disease_association: ctd, mesh, mim, pubmed intact: uniprot, chebi, rnacentral string: uniprot, string_interaction string_interaction: string, uniprot biogrid: entrez, uniprot, refseq, taxonomy bgee: ensembl, uberon, cl, taxonomy, bgee_evidence bgee_evidence: bgee, uberon, cl cellxgene: cl, uberon, mondo, efo, taxonomy cellxgene_celltype: cl, uberon, mondo scxa: cl, uberon, taxonomy, ensembl, scxa_gene_experiment scxa_expression: ensembl, scxa, scxa_gene_experiment scxa_gene_experiment: ensembl, scxa, scxa_expression, cl hpa: ensembl, uniprot, hgnc, entrez, go, uberon, hpa_expression, hpa_pathology, hpa_antibody # Human Protein Atlas gene card: subcellular location (→go), specificity calls, top tissues hpa_expression: hpa, uberon, cellosaurus # per (gene,tissue/cell-line) RNA nTPM + IHC staining; reach genes-in-a-tissue via uberon >> hpa_expression hpa_pathology: hpa # per (gene,cancer) prognostic survival association hpa_antibody: hpa, ensembl # HPA validation antibody (reliability, antigen) rnacentral: uniprot, ensembl, intact, hgnc, refseq, ena, go # go = Rfam-projected GO annotations; rfam_id/rfam_description are attrs on the entry ncrna_disease: hgnc, ensembl, mondo, efo, pubmed # curated ncRNA->disease (LncRNADisease + HMDD); reach from the ncRNA gene ncrna_interaction: hgnc, ensembl, uniprot, pubmed # experimentally-supported ncRNA->protein interactions (NPInter) ncrna_drug: hgnc, ensembl, chembl_molecule, pubchem, pubmed # ncRNA drug-resistance / drug-target (ncRNADrug) reactome: ensembl, uniprot, chebi, go, reactomeparent, reactomechild rhea: chebi, uniprot, go go: ensembl, uniprot, reactome, msigdb, swisslipids, bgee, interpro, goparent, gochild, hpa, rnacentral hpo: clinvar, gencc, mondo, msigdb, orphanet, mim, hmdb, hgnc, hpoparent, hpochild, upheno efo: gwas, mondo, cellxgene, efoparent, efochild, ncrna_disease upheno: hpo, mp, zp, xpo, wbphenotype, fypo, uphenoparent, uphenochild # cross-species phenotype hub. A GENE's model-organism phenotypes are reached THROUGH hpo (genes are NOT linked directly to mp/upheno): >>hgnc>>hpo>>upheno>>mp (mouse), >>hgnc>>hpo>>upheno>>zp (zebrafish), ...>>xpo/wbphenotype/fypo. So gene->human HP phenotypes -> their cross-species equivalents. mp: upheno, mpparent, mpchild # Mammalian Phenotype Ontology (mouse/rat). Reach from a gene via >>hgnc>>hpo>>upheno>>mp (NOT >>hgnc>>mp). zp: upheno, zpparent, zpchild # Zebrafish Phenotype Ontology. Reach from a gene via >>hgnc>>hpo>>upheno>>zp. xpo: upheno, xpoparent, xpochild # Xenopus Phenotype Ontology wbphenotype: upheno, wbphenotypeparent, wbphenotypechild # C. elegans Phenotype Ontology fypo: upheno, fypoparent, fypochild # Fission Yeast Phenotype Ontology uberon: bgee, cellxgene, cellxgene_celltype, swisslipids, uberonparent, uberonchild, hpa, hpa_expression cl: bgee, cellxgene, cellxgene_celltype, scxa, scxa_gene_experiment, clparent, clchild taxonomy: ensembl, uniprot, bgee, biogrid, ctd_gene_interaction, taxparent, taxchild mesh: pharmgkb, ctd, ctd_disease_association, pubchem, mondo, chembl_molecule, meshparent, meshchild eco: ecoparent, ecochild antibody: ensembl, uniprot, mondo, pdb msigdb: hgnc, entrez, go, hpo orphanet: hpo, uniprot, mondo, hgnc, clinvar, mim, mesh mim: clinvar, hpo, mondo, uniprot, ctd_disease_association hmdb: pubchem, hpo, chebi, uniprot collectri: hgnc # transcription factor → target gene interactions esm2_similarity: uniprot # protein structural similarity diamond_similarity: uniprot # protein sequence similarity cellphonedb: uniprot, ensembl, hgnc, pubmed # ligand-receptor pairs for cell-cell communication spliceai: hgnc pdb: uniprot, go, interpro, pfam, taxonomy, pubmed fantom5_promoter: ensembl, hgnc, entrez, uniprot, uberon, cl fantom5_enhancer: ensembl, uberon, cl fantom5_gene: ensembl, hgnc, entrez jaspar: uniprot, pubmed, taxonomy encode_ccre: taxonomy bao: chembl_activity, chembl_assay, baoparent, baochild brenda: uniprot, pubmed, brenda_kinetics, brenda_inhibitor brenda_kinetics: brenda brenda_inhibitor: brenda gtopdb: uniprot, hgnc, gtopdb_ligand, gtopdb_interaction # drug targets (GPCRs, ion channels, enzymes) gtopdb_ligand: pubchem, chebi, chembl_molecule, gtopdb_interaction # ligands/drugs with binding data gtopdb_interaction: gtopdb, gtopdb_ligand, pubmed # target-ligand binding with affinity values civic: entrez, ensembl, civic_variant, civic_evidence, civic_assertion # clinical interpretation of cancer variants civic_variant: civic, clinvar, civic_evidence, civic_assertion civic_evidence: civic_variant, civic, mondo, chembl_molecule, pubmed, clinical_trials civic_assertion: civic_variant, civic, mondo, chembl_molecule intogen: hgnc, entrez, ensembl, mondo, pubmed # cancer driver genes cellosaurus: taxonomy, uniprot, hgnc, mondo, orphanet, clinvar, dbsnp, uberon, cl, chebi, doi, patent, pubmed, depmap_dependency, hpa_expression # cell lines (CVCL) generif: entrez, pubmed # NCBI cited per-gene functional claims (RAG grounding) depmap: entrez, hgnc, ensembl # CRISPR gene essentiality aggregate (cancer dependency / target tractability) depmap_dependency: entrez, cellosaurus # per cell-line gene dependency (effect < -0.5)

FILTER SYNTAX: >>dataset[field operator value]

OPERATORS: == equals >>dataset[field=="value"] != not equals >>dataset[field!="value"]

   greater than     >>dataset[field>value]

< less than >>dataset[field<value]

= greater or equal >>dataset[field>=value] <= less or equal >>dataset[field<=value] contains string match >>dataset[field.contains("value")]

LOGICAL OPERATORS: && AND >>dataset[field1>5 && field2<10] || OR >>dataset[field=="A" || field=="B"] ! NOT >>dataset[!field] or >>dataset[!(field=="value")]

TYPE RULES:

• FLOAT: use decimal point (70.0 not 70)

• INT: no decimal (2 not 2.0)

• STRING: quote values ("Pathogenic", "PHASE3")

• BOOL: true/false (no quotes)

EXAMPLES:

chembl_molecule[highestDevelopmentPhase==4] # approved drugs chembl_molecule[highestDevelopmentPhase>=3] # Phase 3+ clinical_trials[phase=="PHASE3"] go[type=="biological_process"] clinvar[germline_classification=="Pathogenic"] reactome[name.contains("signaling")] gtopdb[type=="gpcr"] # GPCR targets gtopdb[type=="ion_channel"] # ion channel targets gtopdb_ligand[approved==true] # approved drugs only gtopdb_interaction[endogenous==true] # endogenous ligand interactions

Search 70+ biological databases.

SYNTAX: biobtree_search(terms="entity")

BEFORE SEARCHING - Use your training knowledge to plan:

1. What type of entity is this? (disease, process, drug, gene, protein)

2. What is the query asking for? (drugs, genes, function, etc.)

3. What equivalent terms might give better results? (e.g., "temperature homeostasis" is a process → related condition is "fever")

4. Choose best entry point for query type (disease terms for drug queries)

WORKFLOW:

1. Search WITHOUT dataset filter first (discover where entity exists)

2. Use IDs from results with biobtree_map

QUERY PATTERNS (choose based on question):

"DRUG FOR DISEASE/CONDITION X":

• Prefer disease terms (mesh/mondo/efo) over GO terms for drug queries

• If search only returns GO term, search for the related CONDITION instead (e.g., "temperature homeostasis" → search "fever" instead)

• Search disease → mondo → clinical_trials → chembl_molecule

• OR search drug class directly (e.g., "antipyretic", "NSAID", "antibiotic")

• Verify mechanism for top 2-3 drugs only (don't enumerate all proteins!)

"DRUG TARGETS" (use BOTH paths for complete picture):

• chembl: >>chembl_molecule>>chembl_target>>uniprot (mechanism-level)

• pubchem: >>pubchem>>pubchem_activity>>uniprot (protein-level, often 50+ targets)

• Filter approved: >>chembl_molecule[highestDevelopmentPhase==4]

"DISEASE GENES":

• Search disease → mondo/hpo → gencc/clinvar/orphanet → hgnc

"PROTEIN FUNCTION":

• Search protein → uniprot → go/reactome

"MECHANISM QUERIES" (drug-disease):

• Use biobtree_entry to see what's connected (xrefs)

• Check EDGES to see where each xref leads

• Follow connections relevant to your question

• Build chain: Drug → Target → [connections] → Disease

RETURNS: id | dataset | name | xref_count