Tool catalog

Search arXiv for preprints across CS/ML, physics, math, quant-bio, and more. Use for methodology papers, bleeding-edge algorithms, and pre-peer-review results.

bioRxiv + medRxiv preprints. Use for the most recent biology and clinical research (pre-peer-review).

Search ClinicalTrials.gov. Use for trial phase, status, enrollment, primary endpoints, and sponsor. Returns NCT records.

Search ClinVar for clinical significance of genetic variants. Use for variant pathogenicity, allele frequency, and condition associations.

Crossref: canonical DOI registry with bibliographic metadata (journal, ISSN, licence, publisher). Use when the user gives you a DOI to resolve, or when you need authoritative journal/book metadata. Also useful as a backup when OpenAlex is rate-limiting.

Search FDA-approved drug labels. Use for indications, contraindications, dosing ranges, adverse reactions, and black-box warnings. Returns OpenFDA label records.

GitHub: search public repositories by name, description, topics. Use to find official implementations of papers, kernel / compiler / database projects, RFC drafts, and to gauge reproducibility / maintenance for any CS/ML work.

Human Phenotype Ontology. Use to map symptoms to phenotype terms and associated conditions.

Hugging Face Hub: ML models + datasets registry. Use for anything about pretrained models, benchmark datasets, model cards, licences, and downloads/likes signal. First-choice source for CS/ML reproducibility queries.

ICD-10/11 diagnosis coding. Use to map a clinical description to a standardized diagnosis code.

LOINC lab and observation codes. Use when you need the LOINC code for a specific lab test or measurement.

Look up gene records (RefSeq, genomic context, orthologs, expression). Use when a gene symbol needs authoritative NCBI data.

OMIM catalog of Mendelian disorders. Use for gene-disease relationships and inheritance patterns.

OpenAlex: the universal scholarly-works catalog. 260M+ papers across every discipline with citation counts, open-access metadata, and concept tags. Use as the FIRST-CHOICE literature source for any question that isn't obviously biomedical, especially CS/ML, physics, chemistry, earth sciences, social sciences, economics, or humanities.

Query Open Targets for drug-target-disease associations, tractability, and evidence scores. Use for target identification and drug-repurposing hypotheses.

Orphanet rare-disease encyclopedia. Use for orphan disease prevalence, inheritance, and associated genes.

PubChem: NIH compound database with structures (SMILES, InChI), physicochemical properties (MW, XLogP, TPSA), and GHS hazard classifications. FIRST CHOICE for any chemistry question that names a molecule, compound, or drug substance.

Search PubMed for peer-reviewed biomedical literature. Use for clinical research, drug efficacy studies, disease mechanisms, and treatment outcomes. Returns abstracts + PMIDs.

Look up drug nomenclature, ingredients, brand/generic mappings, and drug-drug interactions. Use when you need canonical drug identifiers.

Semantic Scholar: academic papers with citation counts and influence scores. Use when you need citation analysis or cross-discipline coverage.

Search UniProt for protein sequences, functions, domains, PTMs, and cross-references. Use when the question involves a specific protein (gene symbol or accession).

Zenodo: CERN-hosted artifact registry with persistent DOIs. Use to locate versioned datasets, software releases, and supplementary research artifacts that a paper depends on. Especially good for reproducibility questions.

List recent American College of Cardiology (ACC) clinical practice guidelines. Returns ACC-authored guidelines published in JACC and other ACC journals, sorted by date. ACC guidelines cover coronary revascularization, valvular heart disease, chest pain evaluation, cardiac catheterization, and cardiovascular risk assessment.

Fetch detailed content from a specific ADA Standards of Care section by PMID. Retrieves the abstract and, when available via PubMed Central (PMC), a full-text snippet. Use ADA_list_standards_sections first to get PMIDs for each section. All ADA Standards sections are freely available in PMC. Returns title, abstract, full text snippet, and links.

List all sections/chapters of the current ADA Standards of Medical Care in Diabetes. The ADA publishes the Standards of Care annually in Diabetes Care as a free supplement. Each section covers a specific clinical topic (e.g., glycemic goals, pharmacologic treatment, cardiovascular risk management, diabetes technology). Returns section titles, numbers, PMIDs, and PMC links. Use year parameter to access specific editions (default: 2026).

Search ADA (American Diabetes Association) guidelines and publications by topic using PubMed. Searches publications with ADA as corporate author, returning titles, abstracts, PMIDs, and PMC links. Useful for finding ADA recommendations on specific diabetes-related topics such as glycemic targets, insulin therapy, GLP-1 receptor agonists, SGLT2 inhibitors, gestational diabetes, diabetic kidney disease, or diabetes technology.

Predicts blood-brain barrier (BBB) penetrance for a given list of molecules in SMILES format.

Predicts bioavailability endpoints (Bioavailability_Ma, HIA_Hou, PAMPA_NCATS, Caco2_Wang, Pgp_Broccatelli) for a given list of molecules in SMILES format.

Predicts clearance and distribution endpoints (Clearance_Hepatocyte_AZ, Clearance_Microsome_AZ, Half_Life_Obach, VDss_Lombardo, PPBR_AZ) for a given list of molecules in SMILES format.

Predicts CYP enzyme interactions for a given list of molecules in SMILES format.

Predicts nuclear receptor activity endpoints (NR-AR-LBD, NR-AR, NR-AhR, NR-Aromatase, NR-ER-LBD, NR-ER, NR-PPAR-gamma) for a given list of molecules in SMILES format.

Predicts physicochemical properties (molecular weight, logP, hydrogen bond acceptors/donors, Lipinski, QED, stereo centers, TPSA) for a given list of molecules in SMILES format.

Predicts solubility, lipophilicity, and hydration endpoints (Solubility_AqSolDB, Lipophilicity_AstraZeneca, HydrationFreeEnergy_FreeSolv) for a given list of molecules in SMILES format.

Predicts stress response endpoints (SR-ARE, SR-ATAD5, SR-HSE, SR-MMP, SR-p53) for a given list of molecules in SMILES format.

Predicts toxicity endpoints (AMES, Carcinogens_Lagunin, ClinTox, DILI, LD50_Zhu, Skin_Reaction, hERG) for a given list of molecules in SMILES format.

Advanced multi-agent deep literature search system. This is a SEARCH-FIRST system: agents must extensively use Cortexa Tool Mesh literature search tools to gather information, NOT rely on their own knowledge. Required pipeline: (1) query_planner analyzes the query to identify key search aspects and generates 3-8 focused search queries; (2) FIRST call web_foundation_searcher (base web tools only) to produce seeds/sources/keywords; (3) For EACH seed query, parallel call ALL THREE specialized searchers…

Search a curated registry of ~30 major longitudinal cohort studies relevant to aging research worldwide. Contains study metadata including design, sample size, age range, variable categories, and data access information. Use to find the right cohort for a specific research question, such as which studies measure iron intake, grip strength, or walking speed in older adults. Filters by country, study design (longitudinal/cross-sectional), minimum sample size, and specific variable availability.

Fetch the full text (or a detailed snippet) of a specific AHA (American Heart Association) or ACC (American College of Cardiology) guideline from PubMed Central using its PMID. Returns the abstract and, when the article is open-access in PMC, the full guideline text up to 6000 characters covering recommendations, evidence tables, and rationale. Use AHA_list_guidelines or ACC_list_guidelines first to obtain PMIDs. Many recent AHA/ACC guidelines are open-access in PMC.

Search AHA (American Heart Association) and ACC (American College of Cardiology) clinical practice guidelines by topic via PubMed. Covers guidelines published in Circulation, JACC, and other AHA/ACC journals. Useful for finding recommendations on hypertension, heart failure, atrial fibrillation, coronary artery disease, valvular heart disease, lipid management, cardiac arrest, and other cardiovascular conditions.

List recent American Heart Association (AHA) clinical practice guidelines. Returns AHA-authored guidelines and scientific statements published in Circulation and other AHA journals, sorted by date. Covers cardiovascular guidelines on topics including hypertension, heart failure, cardiac arrest, stroke, arrhythmias, and prevention.

Get gene expression experiment datasets from the Allen Mouse Brain Atlas for a given gene. Returns section data sets including plane of section, section thickness, and linked gene info. These datasets contain ISH (in situ hybridization) gene expression images. Example: 'Gad1' returns 22 ISH experiment datasets.

Get detailed information about a brain structure by its Allen Brain Atlas structure ID. Returns full structure record including name, hierarchy path, parent structure, color code. Example: structure_id=382 returns 'Field CA1' in hippocampus.

Search for genes in the Allen Brain Atlas by gene symbol (acronym) or name. Returns gene metadata including Entrez ID, chromosome, homologene ID. Useful for finding gene IDs needed to query expression data. Example: 'Gad1' returns glutamate decarboxylase 1 records for mouse and rat.

Search for brain structures/regions in the Allen Brain Atlas ontology by acronym or name. Returns structure hierarchy, atlas coordinates, and color coding. Example: 'CA1' returns hippocampal Field CA1 across multiple atlases.

Get disease summary information from the Alliance of Genome Resources by Disease Ontology (DO) ID. Returns disease name, definition, synonyms, and classification. The Alliance integrates disease annotations from multiple model organism databases. Example: 'DOID:162' returns cancer with definition and synonyms like 'malignant neoplasm'.

Get genes associated with a disease across all model organisms from the Alliance of Genome Resources. Uses Disease Ontology (DO) IDs to find genes linked to a disease from human, mouse, rat, zebrafish, fly, worm, and other organisms. Includes both direct annotations and inferred associations from model organism phenotypes. Example: 'DOID:162' (cancer) returns TP53, BRCA1, and thousands more.

Get phenotype annotations for a gene from the Alliance of Genome Resources. Returns phenotypes observed when the gene is mutated or knocked out, aggregated from model organism databases. Supports all model organisms (yeast, fly, worm, zebrafish, mouse, rat, frog). Example: 'HGNC:6081' (INS) returns phenotypes like 'Abnormal circulating insulin concentration'.

Search for genes across all model organisms in the Alliance of Genome Resources. Searches by gene symbol, name, or keyword and returns matching genes from human, mouse, rat, zebrafish, fly, worm, yeast, and frog databases. Provides type-ahead suggestions. Example: 'insulin' returns INS (human), Ins1/Ins2 (mouse), ins (zebrafish), etc.

Retrieve AlphaFold MUTAGEN annotations for a given UniProt accession. Returns experimental mutagenesis data mapped onto protein structures from UniProt. The qualifier must be a UniProt ACCESSION (e.g., 'P69905'). Note: Not all proteins have MUTAGEN annotations available in the database.

Retrieve full AlphaFold 3D structure predictions for a given protein. IMPORTANT: The qualifier must be a UniProt ACCESSION (e.g., 'P69905' for HBA_HUMAN). Do NOT use UniProt entry names like 'HBA_HUMAN' - they will cause API errors. To find UniProt accession from a gene/protein name, use `UniProt_search` (e.g., query='gene:HBA' organism='human') or `UniProt_id_mapping` for ID conversion. Returns residue-level metadata including sequence, per-residue confidence scores (pLDDT), and structure down…

Retrieve summary details of AlphaFold 3D models for a given protein. IMPORTANT: The qualifier must be a UniProt ACCESSION (e.g., 'Q5SWX9' for MEIOB_HUMAN). Do NOT use UniProt entry names like 'MEIOB_HUMAN' - they will cause API errors. To find UniProt accession from a gene/protein name, use `UniProt_search` (e.g., query='gene:MEIOB' organism='human') or `UniProt_id_mapping` for ID conversion. Returns lightweight information such as sequence length, coverage, confidence scores, experimental meth…

Get all AlphaMissense pathogenicity scores for a protein by UniProt ID. Returns comprehensive residue-level data for all possible missense variants across the entire protein. Useful for identifying pathogenic hotspots and overall protein vulnerability assessment.

Get AlphaMissense scores for all 20 possible amino acid substitutions at a specific protein position. Useful for saturation mutagenesis analysis and identifying pathogenic hotspots.

Get AlphaMissense pathogenicity score for a specific missense variant. Input: UniProt ID and variant (e.g., 'p.R123H'). Returns score and classification (pathogenic/ambiguous/benign). State-of-the-art for VUS interpretation.

Get detailed information about a specific conda package from a specific channel on Anaconda.org. Returns the package's full metadata including description, all versions, platform availability, download counts, home URL, license, and owner details. Use the format '{channel}/{package_name}' (e.g., 'conda-forge/numpy', 'bioconda/samtools', 'defaults/scipy').

Search Anaconda.org for conda packages across all channels (conda-forge, bioconda, defaults, etc.). Returns matching packages with name, owner/channel, summary, versions, platforms, and download counts. Anaconda.org hosts conda packages for Python, R, and other languages used in scientific computing, data science, and bioinformatics. Bioconda alone has 9,000+ bioinformatics packages.

List Adverse Outcome Pathways (AOPs) from AOPWiki. Returns AOP IDs, titles, and short names. AOPs describe causal chains from molecular initiating events through key events to adverse outcomes, used in toxicology and risk assessment.

Get genes most co-expressed with a query gene from ARCHS4, based on Pearson correlation computed across 300K+ uniformly processed RNA-seq samples. Returns the top N most correlated genes with their Pearson correlation coefficients. Useful for identifying functionally related genes, predicting gene function, and building co-expression networks.

Get gene expression levels across human or mouse tissues and cell lines from ARCHS4 (All RNA-seq and ChIP-seq Sample and Signature Search). Returns box-plot statistics (min, Q1, median, Q3, max) in log2(TPM+1) units for each tissue/cell line, computed from 300K+ uniformly processed RNA-seq samples. Choose type='tissue' for organ/tissue expression or type='cellline' for cell line expression. Results are sorted by median expression (highest first).

Get detailed information about a specific ArrayExpress experiment by its accession ID (E-GEOD, E-MTAB, etc.). Returns complete experiment metadata including title, description, protocols, experimental design, and publication information from the original ArrayExpress database.

Get list of files associated with an ArrayExpress experiment. Returns file metadata including file names, types, sizes, and download paths for raw data files, processed data files, and MAGE-TAB annotation files.

Get sample information for an ArrayExpress experiment. Returns sample metadata including sample names, characteristics (e.g., organism part, developmental stage), experimental factors, and technical details from the original ArrayExpress MAGE-TAB annotations.

Search ArrayExpress experiments - the original functional genomics database from EMBL-EBI. Searches microarray and RNA-seq experiments by keywords, species, or array platform. Returns experiment metadata including accession IDs (E-GEOD, E-MTAB), titles, descriptions, and study information. Note: Some newer ArrayExpress data is now hosted in BioStudies - use BioStudies tools if an accession is not found here.

Get detailed information about a specific artwork from the Art Institute of Chicago collection by its numeric ID. Returns full metadata including title, artist, date, medium, dimensions, provenance, exhibition history, and IIIF image URL. No authentication required. Use ArtIC_search_artworks to find artwork IDs.

Search the Art Institute of Chicago's collection of over 100,000 artworks using its public API. Returns artwork titles, artists, dates, mediums, and collection links. No authentication required. The collection includes Impressionist paintings (Seurat, Monet, Picasso), ancient art, photography, prints, and decorative arts. Useful for art research, museum data analysis, and cultural heritage studies.

Fetch an arXiv paper's PDF and return bounded text snippets around provided terms. Uses markitdown to convert PDF to markdown. All arXiv papers are freely available (no paywall). Useful when key details are in the full text rather than abstract.

Search arXiv for papers by keyword using the public arXiv API. Returns papers with title, abstract, authors, publication date, category, and URL.

Get expression data for a gene across tissues and organs from the Bgee database. Returns where a gene is expressed with expression scores, confidence levels, and quality ratings. Supports RNA-Seq, Affymetrix, EST, and in situ hybridization data types. Requires both an Ensembl gene ID and NCBI taxonomy ID. Example: ENSG00000141510 (TP53) with species 9606 (human) returns expression across 145+ tissues including ventricular zone (score 95.11), ganglionic eminence, and monocytes.

List all species available in the Bgee gene expression database. Returns species with taxonomy IDs, genome versions, and common names. Bgee currently covers 29+ animal species including major model organisms (human, mouse, zebrafish, fruit fly, C. elegans, rat) and additional vertebrates and invertebrates. Useful for discovering which species are available before querying gene expression data.

Search for genes in the Bgee comparative gene expression database across 29+ animal species. Bgee integrates RNA-Seq, Affymetrix, EST, and in situ hybridization data to provide curated expression calls. Search by gene symbol, name, or description. Returns matching genes with species information, biotype, and expression summaries. Example: searching 'TP53' returns tumor protein p53 across human, mouse, zebrafish, and other model organisms.

Get BiGG Models database version and last update date. Returns BiGG version number, API version, and timestamp of last database update. Use for: checking data currency, version control, documentation, reproducibility. Check this to ensure using latest metabolic models data.

Get detailed metabolite information including formula, compartments, and database cross-references. Query from specific model or universal database. Returns metabolite names, formulas, compartment locations, and links to KEGG, MetaCyc, HMDB, ChEBI. Shows which models contain this metabolite. Use for: compound identification, formula lookup, database integration, metabolite annotation. Essential for understanding metabolic networks.

Get detailed information for a specific metabolic model. Returns organism, genome accession, reaction/metabolite/gene counts, and publication reference (PMID). Use for: understanding model scope, checking model currency, finding publications, model selection. Essential metadata before downloading or analyzing a model. Example model IDs: iJO1366 (E. coli), iMM904 (S. cerevisiae), Recon3D (human).

Get all reactions in a metabolic model. Returns reaction IDs, names, and organisms for all biochemical reactions in the model. Use for: analyzing metabolic capabilities, finding specific pathways, reaction enumeration, model comparison. Follow with BiGG_get_reaction for detailed reaction information including stoichiometry and gene-reaction rules.

Get detailed reaction information including stoichiometry, metabolites, gene-reaction rules, and database links. Query from specific model or universal database. Returns reaction equation, participating metabolites with coefficients, GPR (gene-protein-reaction) associations, bounds, and cross-references (KEGG, MetaCyc, BRENDA). Use for: understanding reaction mechanisms, gene associations, flux constraints, pathway analysis. Essential for metabolic modeling.

Get list of all genome-scale metabolic models in BiGG database (85+ models). Returns model IDs, organisms, reaction counts, metabolite counts, and gene counts for bacteria, archaea, and eukaryotes. Models cover E. coli, yeast, human, and other organisms. Use for: discovering available models, finding organism-specific models, comparing model sizes, metabolic modeling projects. Essential first step for flux balance analysis.

Search BiGG database for models, reactions, metabolites, or genes. Returns matching entries with IDs, names, and organism info. Search types: models (find organisms), reactions (find biochemical reactions), metabolites (find compounds), genes (find gene names/IDs). Use for: discovery, finding specific entities, cross-model searches, identifying pathways. Flexible search across entire database.

Get binding affinity data for proteins by PDB structure ID. Returns ligands with measured affinities for the protein structure. Useful for structure-activity relationship analysis when you have co-crystal structures.

Get binding affinity data (Ki, IC50, Kd) for a single protein by UniProt ID. Returns SMILES structures and measured affinities from BindingDB. Essential for drug discovery target analysis. Example: P00533 (EGFR) returns known inhibitors with binding constants.

Get binding affinity data for multiple proteins by UniProt IDs. Returns SMILES and affinities for all matching ligands. Use for comparing binding profiles across protein family members or paralogs.

Find protein targets for a compound by SMILES structure. Returns proteins with binding affinity data for similar compounds. Essential for polypharmacology analysis and off-target prediction.

Search BindingDB for binding affinity data by target gene name or protein name. NOTE: BindingDB REST API is currently unavailable (requests time out). Use ChEMBL_get_target_activities or PubChem BioAssay as alternatives. To query by UniProt ID, use BindingDB_get_ligands_by_uniprot instead.

Search Bioconductor bioinformatics R packages by keyword, topic, or analysis type. Bioconductor provides 2200+ open-source R packages for bioinformatics and computational biology covering RNA-seq, single-cell, proteomics, epigenomics, metabolomics, flow cytometry, imaging, and more. Returns matching packages with title, description, usage count, and relevance score. Powered by R-universe search index. Use this to find packages for specific bioinformatics workflows, then use Bioconductor_get_pac…

Get detailed information about a specific BioImage Archive study by accession number. Returns comprehensive metadata including title, description, imaging methods, organism, and file information. Example: 'S-BIAD634' returns an annotated fluorescence image dataset.

Search the BioImage Archive specifically for biological image datasets (BioImages collection). This targets the BioImages-specific collection at EBI, returning imaging studies with microscopy-specific metadata. Example: 'cell division' finds imaging datasets of cell division processes.

Search the BioImage Archive (EBI BioStudies) for biological imaging datasets. The BioImage Archive hosts open microscopy, imaging, and visualization data from life sciences research. Search by imaging modality (cryo-EM, fluorescence, confocal), organism, technique, or scientific topic. Returns study accessions, titles, and metadata. Example: 'fluorescence microscopy cell' finds fluorescence imaging studies.

Discover and validate biomarkers for a specific disease condition using literature analysis, expression data, pathway enrichment, and clinical validation.

Download a specific file from a BioModels entry or get the download URL for the entire model as a COMBINE archive. Returns download URL and file metadata. Use this to access model files for simulation software (COPASI, CellDesigner, etc.). Specify filename parameter to download a specific file, or omit to get the COMBINE archive containing all files. Find model IDs using biomodels_search.

Get comprehensive metadata for a specific BioModels entry by its model identifier. Returns detailed information including model name, description, publication references, organism, biological processes, SBML level/version, creation/modification dates, and curator annotations. Use this to understand model details, citations, and biological context before downloading or using a model. Find model IDs using biomodels_search (e.g., 'BIOMD0000000469', 'MODEL1707110000').

Get detailed file listing for a specific BioModels entry including file names, types, sizes, and metadata. Returns information about all files associated with the model (SBML files, figures, supplementary data, COMBINE archives). Use this before downloading to see what files are available and their formats. Requires model ID from biomodels_search or BioModels_get_model.

Search for computational biological models in the EBI BioModels database by keyword. Returns models with identifiers, names, formats (typically SBML), and URLs. Use this to find systems biology models related to specific biological processes (e.g., 'glycolysis', 'apoptosis', 'cell cycle'), diseases, or pathways. Find model IDs to use with other BioModels tools for detailed information and downloads.

Search for specific parameters within BioModels entries. Find models containing parameters matching your query (e.g., reaction rates, initial concentrations, kinetic constants). Returns models with parameter names, values, and units. Essential for finding models with specific parameter values or discovering parameter ranges across multiple models. Use this for comparative analysis or parameter estimation studies.

Annotate biomedical text with ontology terms using BioPortal's Annotator (named entity recognition). Scans free text and identifies mentions of biomedical concepts from 900+ ontologies. Useful for extracting disease mentions, drug names, gene functions, phenotypes, and anatomical terms from clinical notes, papers, or abstracts. Example: annotate 'Melanoma is a malignant tumor of melanocytes' to find DOID:1909 (melanoma) and DOID:162 (cancer).

Get detailed information about a specific concept from a BioPortal ontology, including full definition, synonyms, CUI codes, and semantic types. Requires knowing the ontology acronym and concept IRI. Use BioPortal_search_ontology_terms first to find concept IDs, then use this tool for complete details. Example: get details for DOID:1909 (melanoma) from the DOID ontology, or GO:0006915 (apoptotic process) from the GO ontology.

Get children, parents, or ancestors of a specific concept in a BioPortal ontology. Enables hierarchical browsing of ontology term relationships (is-a hierarchy). Use to explore narrower terms (children), broader terms (parents), or full ancestry path (ancestors). Example: get children of DOID:9351 (diabetes mellitus) to find type 1, type 2, gestational diabetes; get ancestors of HP:0001250 (Seizure) to see the full path to root.

Search across 900+ biomedical ontologies in BioPortal (NCBO) for concepts matching a query. BioPortal is the world's largest repository of biomedical ontologies including GO (gene function), HPO (phenotypes), DOID (diseases), CHEBI (chemicals), UBERON (anatomy), SNOMED, MeSH, and 900+ more. Returns matching concepts with labels, IDs, definitions, and synonyms. Optionally filter by specific ontologies. Example: search 'melanoma' to find disease terms across DOID, NCIT, MESH, SNOMED; search 'apop…

Get metadata for a biological database/ontology by its Bioregistry prefix. Returns name, description, homepage, ID pattern, URI format, example IDs, and synonyms. Covers 2600+ resources including UniProt, ChEBI, GO, PDB, Ensembl, HGNC, and many more.

Resolve a compact identifier (prefix:id) to provider URLs across 2600+ biological databases. Given a database prefix (e.g., 'uniprot', 'chebi', 'go', 'pubmed') and an identifier, returns URLs from all known providers. Useful for cross-database linking and identifier resolution.

Search the Bioregistry for databases, ontologies, and resources by keyword. Use to find the correct prefix for identifier resolution, or to discover databases related to a topic (e.g., 'protein', 'gene ontology', 'metabolite').

Get full metadata for a specific bioRxiv or medRxiv preprint by its DOI. Returns comprehensive metadata including title, authors, abstract, publication date, version, category, corresponding author, funding information, and URLs (HTML, PDF, XML). Response time: <1 second. Use when you have a bioRxiv DOI (format: 10.1101/YYYY.MM.DD.XXXXXX). To SEARCH for preprints by keywords, use EuropePMC_search_articles with 'SRC:PPR' filter (fast, relevance-ranked), or web_search with 'site:biorxiv.org'. bio…

List recent bioRxiv or medRxiv preprints by date range. Returns up to 100 preprints posted between the given start and end dates, with title, authors, abstract, DOI, category, and publication status. The bioRxiv API returns results in batches of up to 100; use the cursor parameter for pagination (0 for first page, 100 for second, etc.). Use this to monitor new preprints in a date range or discover recent work in a field. For searching by DOI, use BioRxiv_get_preprint instead. For searching by k…

Get detailed metadata for a specific biological sample from the EBI BioSamples database by accession. Returns sample name, organism, tissue, disease, experimental context, and links to associated data archives (ENA, ArrayExpress, EVA). BioSamples contains 60+ million samples from all major sequence and functional genomics archives. Example: SAMEA104228123 returns a metagenomic sample from the Qiita microbiome project.

Search the EBI BioSamples database by text query across 60+ million biological samples. Returns matching samples with accessions, names, organisms, and key characteristics. Useful for finding source material metadata for sequencing, proteomics, and other experiments. Example: searching 'breast cancer' returns thousands of tumor samples with tissue/disease annotations.

Search the EBI BioSamples database with structured attribute filters. More precise than text search - filters by specific metadata fields like organism, tissue, or disease. Example: attribute='organism', value='Homo sapiens' returns human samples; attribute='disease', value='melanoma' returns melanoma-specific samples.

Get detailed information about a specific BioStudies study by accession number. Returns complete study metadata including attributes, sections, files, and links. Supports various accession formats (e.g., S-BSST123, E-GEOD-12345 for ArrayExpress). HTML responses are converted to Markdown.

Get list of files associated with a BioStudies study. Returns file metadata including paths, sizes, types, and attributes. Files are extracted from the study's section hierarchy.

Search BioStudies repository for biological studies across all collections. BioStudies is a comprehensive repository at EMBL-EBI that hosts diverse study types including genomics, transcriptomics, proteomics, imaging data, and more. Supports full-text search with pagination and sorting. HTML responses are automatically converted to Markdown using markitdown.

Search BioStudies by specific collection (e.g., ArrayExpress, BioImages, EuropePMC). Collections are curated datasets within BioStudies that focus on specific data types or domains. HTML responses are automatically converted to Markdown.

Get detailed information about a specific bioinformatics tool from the ELIXIR Bio.tools registry by its biotoolsID. Returns comprehensive metadata including name, description, homepage, tool type (command-line, web app, database, etc.), EDAM topics and operations, supported input/output data formats, programming languages, operating systems, license, documentation links, and credits. Use biotoolsID values discovered via BioTools_search. Example: 'samtools' for SAMtools, 'blast' for NCBI BLAST.

Search the ELIXIR Bio.tools registry for bioinformatics software tools, databases, and web services. Bio.tools is the comprehensive registry of bioinformatics resources maintained by ELIXIR, containing 30,000+ entries. Returns tool names, descriptions, types, topics, and homepages. Use this to find software for specific bioinformatics tasks (e.g., 'sequence alignment', 'variant calling', 'protein structure prediction'). Example: search 'RNA-seq' to find RNA sequencing analysis tools.

Search the ELIXIR Bio.tools registry for bioinformatics tools by EDAM operation (what the tool does). Returns tools that perform a specific computational operation. Useful operations include: 'Sequence alignment', 'Structure prediction', 'Variant calling', 'Gene expression analysis', 'Phylogenetic inference', 'Protein function prediction', 'Molecular docking', 'Genome annotation', 'Visualisation', 'Data retrieval', 'Statistical calculation', 'Clustering'. Use this to find software for a specifi…

Search the ELIXIR Bio.tools registry for bioinformatics tools by EDAM scientific topic. Returns tools classified under a specific research domain. Useful topics include: 'Proteomics', 'Genomics', 'Transcriptomics', 'Structural biology', 'Phylogenetics', 'Metabolomics', 'Metagenomics', 'Epigenomics', 'Sequence analysis', 'Systems biology', 'Machine learning', 'Molecular interactions', 'Population genetics'. Use this to discover all available software for a specific research field.

Search the ELIXIR Bio.tools registry for bioinformatics resources by tool type. Returns resources of a specific category. Available types: 'Command-line tool', 'Web application', 'Web API', 'Web service', 'Database portal', 'Desktop application', 'Library', 'Plug-in', 'Suite', 'Script', 'Workflow', 'Workbench', 'Ontology', 'Bioinformatics portal'. Use this to find, for example, all database portals or all web APIs for a research domain.

Search nucleotide sequences using NCBI BLAST blastn against nucleotide databases. Requires Biopython (pip install biopython). IMPORTANT: This tool uses NCBI's remote BLAST service which is inherently SLOW - expect 5-30 minutes per query depending on server load. This is normal NCBI behavior, not a bug. For faster results, use smaller databases like 'refseq_select_rna' instead of 'nt'.

Search protein sequences using NCBI BLAST blastp against protein databases. Requires Biopython (pip install biopython). IMPORTANT: This tool uses NCBI's remote BLAST service which is inherently SLOW - expect 5-30 minutes per query depending on server load. This is normal NCBI behavior, not a bug. For faster results, use 'swissprot' or 'pdb' databases instead of 'nr'.

Find BMRB NMR entries associated with a PDB structure. Returns BMRB entry IDs linked to a given PDB accession, with match type (BLAST or author-provided). Useful for finding NMR chemical shift data for a protein with known crystal structure.

Find BMRB NMR entries for a protein using its UniProt accession. Returns NMR data entries associated with the protein, allowing cross-referencing between sequence databases and NMR spectroscopy data.

Get NMR data entry from the Biological Magnetic Resonance Data Bank (BMRB). Returns the full NMR-STAR data for a BMRB entry including chemical shifts, coupling constants, relaxation data, structure restraints, and experimental conditions. BMRB archives NMR spectroscopy data for biological macromolecules (proteins, nucleic acids, carbohydrates) and small molecules. Entry IDs are integers (e.g., 15000 for villin headpiece, 4020 for ubiquitin).

Get the citation/publication information for a BMRB NMR entry in BibTeX format. Returns author list, title, journal, DOI, and year. Useful for citing NMR data sources.

Search BMRB (Biological Magnetic Resonance Data Bank) entries by keyword or molecule name. Returns matching BMRB entries with their IDs and summary information. Use the 'database' parameter to search either macromolecules (proteins, nucleic acids) or metabolomics small molecules.

Get comprehensive enzyme kinetic parameters WITHOUT requiring BRENDA credentials. Retrieves enzyme identity (name, catalytic activity, alternative names) from ExPASy ENZYME and kinetic parameters (Km, kcat, Ki, Vmax, kcat/Km) from SABIO-RK. If BRENDA credentials are set (BRENDA_EMAIL, BRENDA_PASSWORD), additionally fetches optimal pH, optimal temperature, and specific activity from BRENDA. Accepts EC number (e.g., 1.1.1.1) or enzyme name (e.g., alcohol dehydrogenase). Returns aggregated summary…

Get properties and attributes for a biological identifier from BridgeDb. Returns metadata such as molecular formula, molecular weight, InChI, InChIKey, synonyms, and other database-specific attributes. Especially useful for metabolites (HMDB, ChEBI, KEGG compound IDs) to get chemical properties, and for genes to get symbol and name information. System codes: Ch=HMDB, Ce=ChEBI, Ck=KEGG Compound, En=Ensembl, H=HGNC, S=UniProt.

Search for biological identifiers by name using BridgeDb. Enter a gene name, metabolite name, or protein name and get matching identifiers from supported databases. Useful for finding database-specific IDs when you only know the common name. Searches across all database sources available for the specified organism. Returns identifier-database pairs. For example, searching 'glucose' returns matches from MetaCyc, KEGG, and other databases.

Map a biological identifier across databases using BridgeDb. Given an identifier from one database (e.g., HMDB0000122 from HMDB), returns equivalent identifiers in all other supported databases (ChEBI, KEGG, PubChem, Wikidata, CAS, etc.). Supports genes, proteins, metabolites, and other biological entities across 45+ databases and 30+ organisms. System codes: Ch=HMDB, Ce=ChEBI, Ck=KEGG Compound, En=Ensembl, H=HGNC, S=UniProt, L=NCBI Gene, Cpc=PubChem-compound, Ik=InChIKey. Use this when you nee…

Get detailed genome information from BV-BRC (Bacterial and Viral Bioinformatics Resource Center, formerly PATRIC). Returns genome metadata including organism name, taxonomy, genome size, GC content, assembly status, host, disease, and isolation information. BV-BRC is the primary NIAID-funded resource for bacterial and viral pathogen genomics. Example: '83332.12' returns Mycobacterium tuberculosis H37Rv.

Get detailed pathogen protein structure information from BV-BRC by PDB ID. Returns structure metadata including title, resolution, method, gene, organism, UniProt accession, PMID references, sequence, and taxonomic lineage. Useful for structural biology research on pathogen proteins. Example: '6VSB' returns the SARS-CoV-2 spike glycoprotein structure.

Get detailed taxonomy information for a pathogen from BV-BRC by NCBI Taxonomy ID. Returns taxon name, rank, lineage, alternative names, and genome counts. Useful for resolving pathogen taxonomy and understanding classification hierarchy. Example: '2697049' returns SARS-CoV-2 taxonomy with full lineage from Viruses to species.

Search for antimicrobial resistance (AMR) phenotype data in BV-BRC. Returns resistance/susceptibility data for pathogens against specific antibiotics, including MIC values, testing methods, and evidence. Essential for AMR surveillance research. Example: search for methicillin resistance in Staphylococcus aureus.

Search for pathogen epitopes (B-cell and T-cell) in BV-BRC. Returns epitope sequences, types, protein associations, and assay results for vaccine and immunology research. Covers epitopes from IEDB for bacteria and viruses including SARS-CoV-2, influenza, tuberculosis, and other pathogens. Example: search taxon_id 2697049 for SARS-CoV-2 spike glycoprotein epitopes.

Search for genome features (genes, proteins, CDS) in BV-BRC pathogen genomes. Find specific genes like antimicrobial resistance genes (mecA, blaTEM), virulence factors, or any annotated feature across thousands of pathogen genomes. Example: search for 'mecA' gene (methicillin resistance) across all genomes.

Search for pathogen genomes in BV-BRC by organism name or keyword. Returns a list of matching genomes with metadata. Useful for finding bacterial or viral genome assemblies. Example: 'Staphylococcus aureus' returns all S. aureus genome assemblies.

Search for metabolic pathways in pathogen genomes from BV-BRC. Returns KEGG pathway assignments with EC numbers, enzyme descriptions, and genome associations. Useful for understanding pathogen metabolism and identifying potential drug targets. Example: search for pathways in M. tuberculosis (taxon_id 1773).

Search for pathogen protein structures in BV-BRC by organism (taxon_id), gene name, or experimental method. Returns PDB entries with titles, resolution, methods, and references. Covers viral and bacterial protein structures linked to BV-BRC genome annotations. Example: search for all SARS-CoV-2 protein structures with taxon_id 2697049.

Search for specialty genes in BV-BRC including virulence factors, antibiotic resistance genes, drug targets, and human homologs across pathogen genomes. Data sourced from CARD, NDARO, VFDB, PATRIC_VF, and other curated databases. Essential for identifying key pathogenicity and resistance determinants. Example: search for 'mecA' (methicillin resistance gene in Staphylococcus).

Search for functional subsystems (curated groups of functionally related proteins) in BV-BRC pathogen genomes. Returns subsystem classifications including superclass, class, subclass, and specific functional roles. Useful for understanding pathogen functional organization and comparing metabolic capabilities. Example: search for virulence-related subsystems in M. tuberculosis.

Search influenza and pathogen surveillance data in BV-BRC. Returns surveillance samples with host species, geographic location, subtype, and collection metadata. Essential for epidemiological tracking of influenza subtypes (H5N1, H1N1, H3N2) and other monitored pathogens across global regions. Example: search for H5N1 cases in North America.

Search for pathogen taxonomy entries in BV-BRC by keyword. Returns matching taxa with names, ranks, genome counts, and lineage information. Useful for discovering pathogen taxon IDs for use with other BV-BRC tools. Example: 'Mycobacterium' returns the Mycobacterium genus and all its species.

Get CADD scores for all possible substitutions at a genomic position. Returns PHRED scores for A, C, G, T variants at the position. Useful for saturation mutagenesis analysis.

Get CADD scores for all variants in a genomic range (max 100bp). Returns all pre-computed deleteriousness scores in the region. Use for hotspot analysis or exon scanning.

Get CADD deleteriousness score for a specific variant. PHRED scores: >=20 top 1% deleterious (pathogenic threshold ~15-20), >=30 top 0.1%. Input: chromosome, position, ref, alt alleles. Supports GRCh37 and GRCh38.

Give a solution plan to the agent and let it solve the problem. Solution plan should reflect a distinct method, approach, or viewpoint to solve the given question. Call these function multiple times, and each solution plan should start with different aspects of the question, for example, genes, phenotypes, diseases, or drugs, etc. The CallAgent will achieve the task based on the plan, so only give the plan instead of unverified information.

Extract disease-target association scores from cancer biomarkers data. This includes known cancer biomarkers.

Extract disease-target association scores from Cancer Gene Census. This provides curated cancer gene data.

Fetch gene expression values (RNA-seq) for a specific gene across cancer samples in a TCGA or cBioPortal study. Returns per-sample expression values with summary statistics (mean, median, min, max). Output can be combined with survival data for expression-based prognostic analysis. Supports 33 TCGA cancer types and any cBioPortal study with mRNA expression data.

Get summary information for a cancer study including available molecular profiles (mutations, expression, CNV), survival-related clinical attributes, and sample counts. Useful for determining what data is available before querying expression or survival data. Lists all 33 supported TCGA cancer type abbreviations.

Retrieve patient-level overall survival (OS) and disease-free survival (DFS) data from a TCGA or cBioPortal cancer study. Returns per-patient survival times, event status, and age. Data can be directly used with Survival_kaplan_meier or Survival_log_rank_test tools for custom survival analyses. Supports 33 TCGA cancer types (BRCA, LUAD, COAD, GBM, etc.) and 400+ cBioPortal studies.

Search cBioPortal for cancer genomics studies by keyword. Find studies by cancer type, institution, or data type. Returns study IDs that can be used with other CancerPrognosis tools. Covers 400+ studies including all TCGA projects, AACR GENIE, MSK-IMPACT, and institutional cohorts.

Classify a somatic cancer variant using AMP/ASCO/CAP 2017 guidelines (CancerVar). Returns a Tier I–IV assignment: Tier I = Strong Clinical Significance (FDA-approved therapy association), Tier II = Potential Clinical Significance (investigational/preclinical evidence), Tier III = Unknown Clinical Significance, Tier IV = Benign/Likely Benign. Also returns 12 CBP evidence scores and an Oncogenicity Pathogenicity Index (OPAI, 0–1). Input requires genomic coordinates in hg19 or hg38. No API key nee…

Get CATH structural classification for a specific protein domain from PDB. Domains are identified by PDB code + chain + domain number (e.g., 1cukA01). Returns the full CATH hierarchy (Class, Architecture, Topology, Homologous superfamily) and residue count. Example: '1cukA01' returns CATH ID 2.40.50.140.116.1.1.1.1 (Mainly Beta class, Nucleic acid-binding proteins superfamily) with 212 residues.

Get details for a specific functional family (FunFam) within a CATH superfamily. Returns FunFam name, description, member count, seed alignment size, DOPS quality score, and representative domain ID. FunFams represent groups of domains predicted to share the same biological function. Use CATH_list_funfams to browse FunFams within a superfamily, or CATH_get_domain_summary to find which FunFam a specific domain belongs to.

Get CATH protein structure superfamily information by CATH ID. CATH classifies protein domain structures into a four-level hierarchy: Class, Architecture, Topology, Homologous superfamily. Superfamilies group evolutionarily related domains. Returns classification name, number of families, and domain counts. Example: 2.40.50.140 returns 'Nucleic acid-binding proteins' with 227 S35 families and 2,879 total domains.

List functional families (FunFams) within a CATH superfamily. FunFams group protein domains that share the same function, identified by conserved specificity-determining residues. Returns FunFam numbers, names, member counts, and representative domain IDs. Example: superfamily 1.10.510.10 (Globin-like) has 4,524 FunFams including CaM kinase (2,698 members) and Myosin light chain kinase (1,234 members). Use CATH_get_superfamily to find superfamily IDs first.

Get list of cancer studies from cBioPortal

Get all cancer types from cBioPortal including TCGA, Pan-Cancer Atlas, and other studies. Returns cancerTypeId, name, and clinical trial keywords for filtering studies.

Get available clinical attributes for a cancer study. Returns attribute IDs, names, and data types. Use to know what clinical data can be queried (e.g., stage, grade, survival).

Get clinical data for all samples in a study. Returns patient-level data like tumor stage, histology, survival status. Filter by clinical attribute ID for specific data types.

Get detailed information about a specific gene by Entrez Gene ID. Returns gene symbol, aliases, type, and chromosome location.

Get all genes in a specific gene panel. Essential for understanding what genes are covered when analyzing mutation frequency data from targeted sequencing studies.

Get all gene panels used in cBioPortal studies. Gene panels define which genes were sequenced in a study. Use to understand coverage before querying mutation data.

Search for genes by keyword or query (gene symbol or alias). Alias: cBioPortal_search.

Get molecular profiles for a cancer study. Molecular profiles include mutation data, copy number alterations, mRNA expression, etc.

Get mutation data for specific genes in a cancer study. This uses the updated cBioPortal API that requires molecular profiles.

Get all patients in a cancer study

Get all sample lists (cohort definitions) in a cancer study. Sample lists define groups like 'samples with mutations', 'samples with CNA data'. Use for targeted queries.

Get all samples in a cancer study

Retrieve data from a specific CDC dataset on Data.CDC.gov. Requires a dataset ID (view ID) which can be found using cdc_data_search_datasets.

Search the CEDA (Centre for Environmental Data Analysis) data catalogue for UK and global environmental, climate, and atmospheric science datasets. CEDA archives over 450TB of data from atmospheric, earth observation, and climate science research. Returns dataset records with titles, abstracts, time periods, geographic extents, and access information. Essential for finding atmospheric measurements, climate model outputs, satellite data, and Earth observation datasets.

List available cell types in the CellMarker 2.0 database for a given tissue and species. Returns all annotated cell types found in that tissue context. Use this to explore what cell types have been characterized in a specific tissue, or to get an overview of CellMarker's coverage. Supports both normal and cancer cell contexts.

Search the CellMarker 2.0 database for marker genes of a specific cell type. Returns curated lists of marker genes that define a cell type, sourced from single-cell RNA-seq studies and experimental literature. Use this to find canonical markers for cell type annotation, or to build gene sets for cell scoring. Example: 'T cell' returns CD3D, CD3E, CD3G, etc. 'Macrophage' returns CD68, CD163, MARCO, etc.

Search the CellMarker 2.0 database for cell types that express a given marker gene. Returns curated cell type annotations from single-cell RNA-seq studies and experimental literature. CellMarker 2.0 covers >500 cell types across >400 tissue types in human and mouse. Use this to identify which cell types a gene marks, enabling cell type annotation in scRNA-seq analysis. Example: CD3D marks T cells, CD68 marks macrophages, EPCAM marks epithelial cells.

Search the CellMarker 2.0 database for cancer-specific cell markers. Returns marker genes and cell types found in cancer tissue contexts. Use this to identify tumor-specific markers, immune cell markers in the tumor microenvironment, or cancer stem cell markers. Filters results to 'Cancer cell' annotations only. At least one search parameter is required: cancer_type (tissue), gene_symbol, or cell_type.

Get detailed information about a specific cell line using its Cellosaurus accession number (CVCL_ format).

Convert natural language queries to Solr syntax for Cellosaurus API searches. Uses semantic similarity to map terms to appropriate fields.

Search Cellosaurus cell lines using the /search/cell-line endpoint. Supports Solr query syntax for precise field-based searches.

Get the list of plates in a Cell Painting screen from the Image Data Resource (IDR). Returns plate IDs and names for the given screen. Use CellPainting_search_screens first to find valid screen IDs. Example: Get all plates in idr0016 screenA (screen_id=1251).

Get well-level metadata and image links for a specific plate in a Cell Painting experiment from the Image Data Resource (IDR). Returns well IDs, row/column positions, well URLs, and links to microscopy images. Use CellPainting_get_screen_plates to find valid plate IDs. Example: Get the first 5 wells of plate 5104 from idr0016.

List available Cell Painting screens/studies in the Image Data Resource (IDR). Returns screen names, IDs, descriptions, and URLs. Automatically filters to Cell Painting and morphological profiling studies (e.g. idr0016 Wawer ~30,000 compounds, JUMP-CP). Use the optional query parameter to further filter by keyword. Example: Discover which Cell Painting datasets are available in IDR.

Download original H5AD (HDF5-based AnnData) files from CELLxGENE datasets or get their URIs. Access unprocessed data from individual studies with complete metadata and analysis results. Requires dataset_id from CELLxGENE Discover. Note: Files can be large (GBs). Use for: accessing raw data, reproducibility, offline analysis, custom processing pipelines.

Query cell metadata from CELLxGENE Census (50M+ human/mouse single cells). CRITICAL: obs_value_filter is REQUIRED - unfiltered queries will timeout. Common filters: tissue_general (brain, heart, lung, liver, blood, kidney, skin, eye, intestine), cell_type (T cell, B cell, neuron, macrophage, fibroblast), disease (normal, COVID-19, Alzheimer disease, cancer). Start with: obs_value_filter='tissue_general == "lung" and disease == "normal"'. Returns cell type, tissue, disease, donor info. Use for:…

Get list of available CELLxGENE Census versions with release dates and descriptions. The Census contains single-cell RNA-seq data from 50M+ cells (human, mouse, non-human primates). Latest LTS release: 2025-11-08. Prerequisites: Requires 'cellxgene-census' package (install: pip install Cortexa Tool Mesh[singlecell]). Use for: checking available data versions, selecting stable vs latest builds, understanding data updates.

Access pre-calculated cell embeddings (scVI, Geneformer) from CELLxGENE Census. Returns available embedding names or specific embedding data. Embeddings enable rapid visualization and analysis without recomputation. Use for: UMAP/t-SNE visualization, cell similarity analysis, transfer learning.

Query gene expression data from CELLxGENE Census (50M+ cells, 60K+ genes). CRITICAL: At least one filter REQUIRED - unfiltered queries timeout. Start with: obs_value_filter='tissue_general == "lung" and disease == "normal"' AND var_value_filter='feature_name in ["TP53", "EGFR"]'. Returns AnnData summary (dimensions, metadata). For full matrix data, use Python API with sufficient memory.

Query gene (variable) metadata from CELLxGENE Census. Returns gene symbols, Ensembl IDs, feature types, and summary statistics. Filter by gene name, feature type, or expression characteristics. Use for: finding genes of interest, validating gene symbols, exploring feature presence across datasets.

Get feature presence matrix showing which genes are measured in which datasets. Returns sparse matrix dimensions and density. Useful for understanding data completeness and selecting datasets with genes of interest. Use for: checking gene coverage, dataset selection, quality assessment.

Get cofactor access tunnel data for a PDB structure from ChannelsDB. Specifically detects tunnels that provide access pathways for cofactors and small molecules to reach enzyme active sites or binding pockets. Each channel includes geometric profile data (radius along the path, 3D coordinates), physicochemical properties (charge, hydrophobicity, polarity), and the residue layers that line the tunnel. Use ChannelsDB_get_channels_pdb for a complete view of all channel types including transmembran…

Get protein channel, tunnel, and pore data for a PDB structure from ChannelsDB. ChannelsDB is a comprehensive database of channels (tunnels, pores, and voids) found in biomacromolecular structures deposited in the Protein Data Bank. Returns channel geometry profiles (radius, distance along path, 3D coordinates), physicochemical properties (charge, hydrophobicity, polarity, mutability), residue layers lining each channel, and expert annotations when available. Useful for studying transport pathw…

Get detailed information about a chemical entity from ChEBI (Chemical Entities of Biological Interest) by its CHEBI ID. Returns the compound name, definition, synonyms, molecular formula, mass, InChIKey, SMILES, charge, and star rating (curation quality: 3=manually curated, 2=checked, 1=unchecked). ChEBI is maintained by EBI and is the standard reference for small molecules in biology. Example: CHEBI:15365 returns acetylsalicylic acid (aspirin).

Get the ontology children (is-a, has-part, has-functional-parent, etc.) of a ChEBI compound. ChEBI uses a rich ontology with relationships like 'is a', 'has part', 'has role', 'has functional parent', and 'is conjugate base/acid of'. This enables navigation of the chemical classification hierarchy. Example: CHEBI:15365 (aspirin) children include NCX-4040 (has functional parent), acetylsalicylate (conjugate base), and Yosprala (has part).

Search the ChEBI database for chemical entities by name, formula, or keyword. Uses Elasticsearch-powered full-text search across compound names, synonyms, definitions, and formulas. Returns matching compounds with IDs, names, formulas, and masses. Note: smiles and inchikey are not available from the search endpoint (use ChEBI_get_compound for structural data). Compound names are HTML-stripped. ChEBI contains 195,000+ chemical entities of biological interest.

Compute the synthetic accessibility (SA) score for a molecule supplied as a SMILES string, using the RDKit SA_Score contribution module. The algorithm encodes synthetic complexity from fragment frequency statistics across drug-like compounds. Scores run from 1 (minimal synthetic effort, simple building blocks) to 10 (highly complex, exotic or multi-step routes); practical benchmarks: <=3 readily accessible, 3-6 moderate synthetic challenge, >6 significant complexity. Accepts any SMILES parseabl…

Extract disease-target association scores specifically from ChEMBL database. ChEMBL provides bioactivity data for drug-target interactions.

Get detailed information about a specific activity by its activity ID. Activity IDs are found in the results from ChEMBL_search_activities or ChEMBL_get_target_activities.

Get detailed information about an assay by its ChEMBL assay ID. To find an assay ID, use ChEMBL_search_assays or ChEMBL_get_target_assays.

Get all activity data for an assay by ChEMBL assay ID. Returns bioactivity measurements from the specified assay. To find an assay ID, use ChEMBL_search_assays or ChEMBL_get_target_assays.

Get compound record information by ChEMBL compound record ID.

Get all activities for a compound record by compound record ID. Returns bioactivity measurements for the specified compound record.

Get detailed information about a drug by its ChEMBL drug ID. Includes approval status, indications, and mechanisms. To find a drug ID, use ChEMBL_search_drugs with a drug name.

Get mechanisms of action for a drug by ChEMBL drug ID or drug name. Accepts drug_chembl_id (e.g., 'CHEMBL1201581') or drug_name (e.g., 'trastuzumab') — drug_name triggers automatic ChEMBL ID lookup.

Get detailed information about a molecule by its ChEMBL ID. Returns molecule properties, structures, synonyms, and related data.

Get molecular structure image (SVG or PNG format) for a molecule by ChEMBL ID. Returns the image URL and metadata.