Metabolomics Workbench Tools

Configuration File: metabolomics_workbench_tools.json Tool Type: Local Tools Count: 8

This page contains all tools defined in the metabolomics_workbench_tools.json configuration file.

Available Tools

MetabolomicsWorkbench_find_studies_by_phenotype (Type: MetabolomicsWorkbenchTool)

Discover Metabolomics Workbench studies matching a phenotype/experimental profile via the METSTAT…

MetabolomicsWorkbench_find_studies_by_phenotype tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_find_studies_by_phenotype

  • Type: MetabolomicsWorkbenchTool

  • Description: Discover Metabolomics Workbench studies matching a phenotype/experimental profile via the METSTAT context. Filter the study catalog by any combination of: analysis type (e.g. ‘MS’, ‘NMR’), polarity (POSITIVE/NEGATIVE), chromatography (e.g. ‘HILIC’, ‘Reverse phase’), species (e.g. ‘Human’, ‘Mouse’), sample source (e.g. ‘Blood’, ‘Urine’, ‘Liver’), disease (e.g. ‘Diabetes’, ‘Cancer’), KEGG id, and RefMet metabolite name. Every filter is optional and empty filters act as wildcards (at least one filter is required). Returns the matching studies (study id, title, and the matched species/source/disease context). Example: species=’Human’, source=’Blood’, disease=’Diabetes’ -> 28 studies including ST003897 ‘Postprandial Plasma Lipidomic Changes…’.

Parameters:

  • analysis ([‘string’, ‘null’]) (optional) Analysis type filter (e.g. ‘MS’, ‘NMR’, ‘LC-MS’).

  • polarity ([‘string’, ‘null’]) (optional) Ionization polarity filter (‘POSITIVE’ or ‘NEGATIVE’).

  • chromatography ([‘string’, ‘null’]) (optional) Chromatography type filter (e.g. ‘HILIC’, ‘Reverse phase’).

  • species ([‘string’, ‘null’]) (optional) Subject species filter (e.g. ‘Human’, ‘Mouse’, ‘Rat’).

  • source ([‘string’, ‘null’]) (optional) Sample source / specimen filter (e.g. ‘Blood’, ‘Urine’, ‘Liver’, ‘Feces’).

  • disease ([‘string’, ‘null’]) (optional) Disease / condition filter (e.g. ‘Diabetes’, ‘Cancer’, ‘Obesity’).

  • kegg_id ([‘string’, ‘null’]) (optional) KEGG compound id filter (e.g. ‘C00031’).

  • refmet_name ([‘string’, ‘null’]) (optional) RefMet standardized metabolite name filter (e.g. ‘Glucose’, ‘Cholic acid’).

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_find_studies_by_phenotype",
    "arguments": {
    }
}
result = tu.run(query)

MetabolomicsWorkbench_get_compound_by_pubchem_cid (Type: MetabolomicsWorkbenchTool)

Get metabolite information by PubChem compound ID (CID). Useful for cross-referencing with PubChe…

MetabolomicsWorkbench_get_compound_by_pubchem_cid tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_get_compound_by_pubchem_cid

  • Type: MetabolomicsWorkbenchTool

  • Description: Get metabolite information by PubChem compound ID (CID). Useful for cross-referencing with PubChem data.

Parameters:

  • input_value (string) (required) PubChem compound ID (CID) as a string (e.g., ‘311’ for citric acid).

  • output_item (string) (optional) Type of output to return.

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_get_compound_by_pubchem_cid",
    "arguments": {
        "input_value": "example_value"
    }
}
result = tu.run(query)

MetabolomicsWorkbench_get_gene_protein (Type: MetabolomicsWorkbenchTool)

Look up a Metabolomics Workbench gene or protein (MGP) annotation record linking gene/protein ide…

MetabolomicsWorkbench_get_gene_protein tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_get_gene_protein

  • Type: MetabolomicsWorkbenchTool

  • Description: Look up a Metabolomics Workbench gene or protein (MGP) annotation record linking gene/protein identifiers to the Metabolomics Workbench. Set entity=’gene’ (default) or entity=’protein’; id_type selects the lookup namespace. Gene records (entity=’gene’) return gene_symbol, gene_id, gene_name, synonyms, chromosome/map_location, MGP id, and a summary. Protein records (entity=’protein’) return UniProt id, gene_symbol, species, mRNA/RefSeq ids, protein entry name, sequence length and the amino-acid sequence. Examples: entity=’gene’, id_type=’gene_symbol’, input_value=’acaca’ -> ACACA ‘acetyl-CoA carboxylase alpha’, gene_id 31, MGP000016; entity=’protein’, id_type=’uniprot_id’, input_value=’Q13085’ -> ACACA_HUMAN, NM_198839, NP_942136, 2346 aa.

Parameters:

  • input_value (string) (required) The identifier to look up (e.g. gene symbol ‘acaca’, UniProt id ‘Q13085’, mgp_id ‘MGP000016’).

  • entity ([‘string’, ‘null’]) (optional) Which record type to fetch: ‘gene’ (default) or ‘protein’.

  • id_type ([‘string’, ‘null’]) (optional) Namespace of input_value. For genes: gene_symbol (default), gene_id, gene_name, mgp_id, refseq_id. For proteins: uniprot_id (default), gene_symbol, mgp_id, refseq_id, gene_id.

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_get_gene_protein",
    "arguments": {
        "input_value": "example_value"
    }
}
result = tu.run(query)

MetabolomicsWorkbench_get_refmet_info (Type: MetabolomicsWorkbenchTool)

Get RefMet standardized nomenclature for a metabolite. RefMet provides consistent, standardized m…

MetabolomicsWorkbench_get_refmet_info tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_get_refmet_info

  • Type: MetabolomicsWorkbenchTool

  • Description: Get RefMet standardized nomenclature for a metabolite. RefMet provides consistent, standardized metabolite names across studies.

Parameters:

  • input_value (string) (required) Metabolite name to look up in RefMet (e.g., ‘Glucose’, ‘Palmitic acid’).

  • output_item (string) (optional) Type of information to return.

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_get_refmet_info",
    "arguments": {
        "input_value": "example_value"
    }
}
result = tu.run(query)

MetabolomicsWorkbench_get_study (Type: MetabolomicsWorkbenchTool)

Get metadata and information about a metabolomics study by its study ID. Returns study summary in…

MetabolomicsWorkbench_get_study tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_get_study

  • Type: MetabolomicsWorkbenchTool

  • Description: Get metadata and information about a metabolomics study by its study ID. Returns study summary including title, subject species, analysis type, and metabolites.

Parameters:

  • study_id (string) (required) Metabolomics Workbench study ID (e.g., ‘ST000001’, ‘ST000100’).

  • output_item (string) (optional) Type of information to return. Options: ‘summary’ (study overview), ‘factors’ (experimental factors), ‘analysis’ (analysis methods), ‘metabolites’ (metabolite list), ‘data’ (full data matrix).

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_get_study",
    "arguments": {
        "study_id": "example_value"
    }
}
result = tu.run(query)

MetabolomicsWorkbench_search_by_exact_mass (Type: MetabolomicsWorkbenchTool)

Search metabolites by exact molecular mass. Useful for identifying unknown metabolites from high-…

MetabolomicsWorkbench_search_by_exact_mass tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_search_by_exact_mass

  • Type: MetabolomicsWorkbenchTool

  • Description: Search metabolites by exact molecular mass. Useful for identifying unknown metabolites from high-resolution mass spectrometry.

Parameters:

  • mass_value (number) (required) The exact mass value to search for in Daltons (e.g., 180.0634).

  • tolerance (number) (optional) Mass tolerance in Daltons for the search.

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_search_by_exact_mass",
    "arguments": {
        "mass_value": "example_value"
    }
}
result = tu.run(query)

MetabolomicsWorkbench_search_by_mz (Type: MetabolomicsWorkbenchTool)

Search metabolites by m/z (mass-to-charge ratio) value from mass spectrometry data. Essential for…

MetabolomicsWorkbench_search_by_mz tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_search_by_mz

  • Type: MetabolomicsWorkbenchTool

  • Description: Search metabolites by m/z (mass-to-charge ratio) value from mass spectrometry data. Essential for metabolite identification from MS experiments.

Parameters:

  • mz_value (number) (required) The m/z value to search for (e.g., 180.0634 for glucose [M+H]+).

  • adduct (string) (optional) Adduct type. Common values: ‘M+H’ (protonated), ‘M-H’ (deprotonated), ‘M+Na’ (sodiated), ‘M+K’ (potassiated).

  • tolerance (number) (optional) Mass tolerance in Daltons for the search.

  • database (string) (optional) Database to search: ‘MB’ (Metabolomics Workbench, default), ‘LIPIDS’, or ‘REFMET’.

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_search_by_mz",
    "arguments": {
        "mz_value": "example_value"
    }
}
result = tu.run(query)

MetabolomicsWorkbench_search_compound_by_name (Type: MetabolomicsWorkbenchTool)

Search for a metabolite/compound by its name using RefMet nomenclature. Returns standardized comp…

MetabolomicsWorkbench_search_compound_by_name tool specification

Tool Information:

  • Name: MetabolomicsWorkbench_search_compound_by_name

  • Type: MetabolomicsWorkbenchTool

  • Description: Search for a metabolite/compound by its name using RefMet nomenclature. Returns standardized compound information including formula, exact mass, and classification. Use this for finding metabolites by common name.

Parameters:

  • input_value (string) (optional) Compound/metabolite name to search (e.g., ‘Glucose’, ‘Cholesterol’, ‘Palmitic acid’). Aliases: compound_name, name.

  • compound_name (string) (optional) Alias for input_value.

  • output_item (string) (optional) Type of output to return.

Example Usage:

query = {
    "name": "MetabolomicsWorkbench_search_compound_by_name",
    "arguments": {
    }
}
result = tu.run(query)