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HolobiomicsLab

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• 7.4k skills
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• 15 hours ago last updated

1. ▌
   Factorial Design Anova · holobiomicslab

   Use when you have a LipidomicsExperiment object with samples grouped by a categorical variable (e.
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2. ▌
   Hdf5 Schema Validation · holobiomicslab

   Use when after converting proprietary vendor mass spectrometry files (Thermo .raw, Agilent .d, Bruker .d, or mzML) to MZA HDF5 format using the MZA executable.
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3. ▌
   Imzml Metadata Parsing · holobiomicslab

   Use when you have received paired .imzML (XML metadata) and .ibd (binary data) files from an Imaging Mass Spectrometry instrument and need to discover the imaging geometry, m/z calibration, and scan coordinate system before extracting mass images or computing total ion chromatograms (TIC).
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4. ▌
   Ion Feature Extraction · holobiomicslab

   Use when you have raw mass-spectrometry data files (mzML, mzXML, or vendor formats) from untargeted metabolomics experiments and need to identify and quantify differential metabolic ion peaks.
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5. ▌
   JSON Format Conversion · holobiomicslab

   Use when when you have extracted file metadata or scan summaries as R list objects from .raw files using readFileHeader(), readIndex(), or readSpectrum(), and need to persist them to disk, share them across systems, or feed them into downstream tools that consume JSON (e.
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6. ▌
   Kegg Database Querying · holobiomicslab

   Use when you have identified two or more organisms (via their KEGG organism codes, e.g., 'hsa' for Homo sapiens) and need to retrieve their complete metabolic pathway and reaction datasets as a prerequisite for network reconstruction or comparative metabolic analysis.
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7. ▌
   Lipid Library Curation · holobiomicslab

   Use when you have obtained MobiLipid or a similar IM-MS lipidomics package that bundles a CCS reference library for labeled lipids, and you need to verify library integrity, validate that all expected lipid species are present with plausible numeric CCS values, and prepare a canonical curated.
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8. ▌
   Lipidomics Data Mining · holobiomicslab

   Use when when you have quantitative lipidomics data (either from Skyline CSV export or numerical matrix format) with sample annotations and a biological grouping variable (e.
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9. ▌
   Mzml Output Validation · holobiomicslab

   Use when after running AirdPro's CLI conversion pipeline (run-cli.sh with -i and -o arguments) to confirm the vendor raw file conversion to mzML has succeeded.
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10. ▌
    Peak Table Compilation · holobiomicslab

    Use when after peak detection has been applied to untargeted or targeted mass spectrometry data and peaks have been matched against metabolite databases and reference spectra.
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11. ▌
    Smiles Format Handling · holobiomicslab

    Use when when you have molecular structures in proprietary or non-standard formats (e.
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12. ▌
    Software Smoke Testing · holobiomicslab

    Use when after successful compilation or artifact generation (e.g., after `mvn clean package`, `make`, or `python setup.py build`) and before promoting the artifact to testing, distribution, or end-user deployment.
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13. ▌
    Uml Diagram Generation · holobiomicslab

    Use when when you have access to a modular object-oriented codebase and need to map its class hierarchy, composition relationships, and extension mechanisms (abstract classes, interfaces, factory patterns) in order to guide developers toward specific modules to improve or extend.
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14. ▌
    Migration Time Extraction · holobiomicslab

    Use when you have OnDiskMSnExp CE-MS objects with known marker compounds (e.g., Paracetamol EOF marker) and need to extract their migration time positions to establish a calibration reference.
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15. ▌
    Signal Quality Assessment · holobiomicslab

    Use when you have imported raw MSI spectral data in imzML format and need to improve signal-to-noise ratio before performing mean intensity calculations, ROI analysis, or database annotation.
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16. ▌
    Ei Spectrum Normalization · holobiomicslab

    Use when you have raw electron ionization mass spectra (m/z and intensity pairs) that you intend to match against a library using the Identity (EI Normal) or Similarity (EI Simple) algorithms. Different ionization runs and instrument conditions produce spectra with varying absolute intensities;
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17. ▌
    Library Object Validation · holobiomicslab

    Use when after applying mspcompiler pipeline transformation steps (e.g., reorganize_mona, assign_smiles, assign_ri, read_multilibs, separate_polarity, complete_mgf) to confirm the operation succeeded without data loss or structural corruption.
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18. ▌
    Tandem Ms Peak Assignment · holobiomicslab

    Use when when you have experimental tandem MS spectra (with peak m/z and intensity values) and need to annotate each peak with its chemical formula (SCARF) or molecular fragment origin (ICEBERG), particularly for structural elucidation campaigns where understanding the fragmentation pathway is.
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19. ▌
    Candidate Formula Ranking · holobiomicslab

    Use when you have an observed m/z value from mass spectrometry imaging and need to assign a chemical formula with high confidence.
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20. ▌
    Candidate Match Retrieval · holobiomicslab

    Use when when you have a query MS/MS spectrum (m/z and intensity pairs) and need to find potential structural analogues or exact matches in a large spectral library. Apply this skill after preprocessing your spectra (e.
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21. ▌
    Chemical Ontology Mapping · holobiomicslab

    Use when your analysis has produced both in silico structural predictions (e.
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22. ▌
    Conditional Routing Logic · holobiomicslab

    Use when you have received a USI string (formatted as mzspec:<namespace>:<resource>:<identifier_type>:<identifier>) and need to retrieve the corresponding mass spectrum data.
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23. ▌
    Custom Database Searching · holobiomicslab

    Use when when you have LC-MS/MS data in Mascot Generic Format (mgf) files and need to identify compounds against a curated custom database (e.g., prepared using CFM-id for a specific metabolite class or organism) rather than relying on in-built commercial spectral libraries alone.
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24. ▌
    Data Integrity Assessment · holobiomicslab

    Use when immediately after importing raw mass spectrometry data from supported formats (mzML, mzXML, msp, metabolomics-USI, MGF, JSON) and before performing spectral similarity comparisons or statistical analysis.
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25. ▌
    Feature Table Gap Filling · holobiomicslab

    Use when you have an aligned feature table from untargeted LC-MS with missing intensity values (NA or zero entries) for features that are present in some samples but fell below detection threshold in others.
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26. ▌
    Formula Database Querying · holobiomicslab

    Use when you have calibrated m/z peak lists, configured adduct transformations (e.g., [M+H]+, [M+Na]+, [M-H]−), and need to annotate peaks with molecular formulae from KEGG, PubChem, or custom databases.
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27. ▌
    Gensim Pipeline Execution · holobiomicslab

    Use when you have an MS2 spectral file (MGF format) from LC-MS/MS metabolomics analysis and need to discover latent topics across fragmentation patterns for unsupervised characterization. Use it as the prerequisite step before topic visualization in the ms2lda web interface.
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28. ▌
    Imzml File Format Parsing · holobiomicslab

    Use when you have acquired imaging mass spectrometry (IMS) data stored in imzML format (accompanied by an .ibd ion binary data file) and need to load it into a Python-based spatial metabolomics workflow.
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29. ▌
    Infoence Loss Composition · holobiomicslab

    Use when when training embeddings from MS/MS spectra data where you need both discriminative power (to distinguish similar spectra) and reconstruction accuracy (to preserve peak and metadata information).
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30. ▌
    Input Type Classification · holobiomicslab

    Use when a web application receives mass spectrometry data through heterogeneous identifier formats and must automatically determine which loader (Task ID, USI, or FBMN) should process the input.
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31. ▌
    Ion Mobility Peak Picking · holobiomicslab

    Use when when you have extracted ion mobilograms from DIA-MS experiments and need to automatically identify peak boundaries and apex positions in the ion mobility dimension.
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32. ▌
    Isotope Adduct Annotation · holobiomicslab

    Use when after completing peak picking, sample alignment, and before final MS2 spectrum extraction, when you have identified individual ion peaks across samples and need to link isotopic variants (e.
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33. ▌
    Isotopic Pattern Matching · holobiomicslab

    Use when after feature detection has produced candidate formula–adduct pairs and their corresponding m/z values, but before final compound identification.
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34. ▌
    Khipu Grid Offset Mapping · holobiomicslab

    Use when you have a set of ions detected in LC-MS data that are suspected to derive from the same neutral compound via different isotope and adduct patterns. Use this skill after ions have been matched to isotope and adduct patterns and assigned to grid positions (isotope row and adduct column).
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35. ▌
    Lc Ms Peak Quantification · holobiomicslab

    Use when after a CNN-Transformer peak detection model has been run on LC-MS ROI images and has output predicted peak locations with confidence scores.
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36. ▌
    Lcms Data Format Handling · holobiomicslab

    Use when you have raw LC-MS data from a vendor instrument or in netCDF format and need to ingest it into SLAW or similar untargeted LC-MS workflows. Use this skill when raw data must be converted to mzML, validated for centroiding and polarity uniformity, and prepared for peak-picking dispatch.
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37. ▌
    Library Import Validation · holobiomicslab

    Use when you have raw .msp spectral library files (e.g., from MassBank or custom sources) and need to convert them into a structured CSV library format for use in metabolite annotation.
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38. ▌
    Lipid Coverage Assessment · holobiomicslab

    Use when after hierarchical fragmentation library matching has produced candidate lipid annotations for a multi-species LC-MS/MS dataset, and you have applied retention time–based filtering rules (e.
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39. ▌
    Metabdata Object Handling · holobiomicslab

    Use when you have a raw peak-picked untargeted LC-MS dataframe with columns containing mass-to-charge (m/z), retention time (rt), feature identifiers, adduct annotations, and sample measurements in non-standard column names or mixed column sets.
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40. ▌
    Metabolic Network Mapping · holobiomicslab

    Use when you have an untargeted metabolomics feature table (with m/z, retention time, and statistical significance values) and want to predict which metabolic pathways and functional modules are active in your sample, but you lack confident metabolite identifications or wish to bypass the.
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41. ▌
    Mpactr Filter Application · holobiomicslab

    Use when you have a preprocessed peak table from tandem MS/MS data (e.
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42. ▌
    Mrm Transition Extraction · holobiomicslab

    Use when you have raw LC-MS/MS data in MRM acquisition mode and need to systematically identify and catalog all precursor m/z and corresponding product m/z values for each transition monitored during data collection.
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43. ▌
    Ms Ms Spectrum Prediction · holobiomicslab

    Use when you have MS/MS spectra (in MGF format) with required metadata fields (TITLE, PRECURSOR_MZ, PRECURSOR_TYPE, COLLISION_ENERGY) and need to predict candidate molecular formulas ranked by confidence.
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44. ▌
    Ms2 Spectra Tic Filtering · holobiomicslab

    Use when after concatenating replicate MS/MS spectra for each precursor feature (m/z and retention time), use this skill when you have multiple replicate scans per feature and need to reduce spectral count while preserving the highest-intensity, most-reliable spectra.
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45. ▌
    Ms2lda Feature Annotation · holobiomicslab

    Use when after creating a GNPS mass spectral molecular network and running an MS2LDA experiment, use this skill when you want to identify and visualize which substructural motifs (Mass2Motifs) are shared across clustered spectra, particularly to highlight fragmentation pattern similarities between.
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46. ▌
    Multi Tool Schema Mapping · holobiomicslab

    Use when you have peak/feature table outputs from one or more peak-picking tools (MZmine, XCMS, MS-DIAL, Compound Discoverer) with different column names and metadata structures, and you need to ingest them into LipidMatch or another unified lipidomics pipeline that requires consistent column.
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47. ▌
    Pathway Score Aggregation · holobiomicslab

    Use when you have a metabolite intensity matrix (samples × metabolites) or gene expression matrix (samples × genes) with corresponding pathway definitions (pathway IDs mapped to feature sets), and you need to rank pathways by activity level to identify which biological processes are most affected.
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48. ▌
    Peptide Spectrum Matching · holobiomicslab

    Use when when you have high-resolution tandem mass spectrometry data (in mzML or mzXML format) and a spectral library, and need to identify peptides including those with post-translational modifications.
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49. ▌
    Proteome Dataset Handling · holobiomicslab

    Use when you have a collection of MS/MS spectra in MGF format and need to prepare them for GPU-based clustering. Dataset size and available GPU memory are critical: use GTX 1080Ti for smaller proteome datasets; use GTX 3090 for datasets like PXD000561 that exceed GTX 1080Ti capacity.
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50. ▌
    Python Workflow Scripting · holobiomicslab

    Use when you have raw mass spectrometry spectral data in common formats (MGF, MSP, mzML, mzXML, JSON) that requires standardized metadata cleaning, validation, and peak filtering before comparative analysis. Use this skill when you need to encode data quality constraints (e.
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51. ▌
    R Workflow Implementation · holobiomicslab

    Use when you have raw mass spectrometry data in mzXML, mzML, or netCDF format from untargeted LC/HRMS analysis that has been pre-processed by IDSL.
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52. ▌
    Resolver Url Construction · holobiomicslab

    Use when when you have a USI string (comprising dataset identifier, spectrum index, and optional library reference) and need to generate a stable, machine-readable link that resolves to interactive spectrum visualization or programmatic access.
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53. ▌
    Retention Time Prediction · holobiomicslab

    Use when you have MS1-formatted mass spectrometry files from a liquid chromatography–mass spectrometry (LC-MS) experiment and need to predict the retention time of peptide ions without relying on spectral libraries, empirical models, or manual feature engineering.
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54. ▌
    Schema Compliance Testing · holobiomicslab

    Use when when uploading or ingesting a new paired omics project JSON document into the Pairing Omics Data Platform, or when programmatically submitting projects via the OpenAPI interface. Apply this skill before persisting the document to disk or indexing it for search.
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55. ▌
    Siamese Network Inference · holobiomicslab

    Use when you have a collection of cleaned MS/MS spectra (in formats like mzML, mgf, msp, mzxml, or json) and need to predict molecular structural similarities between spectrum pairs without pre-computing RDKit fingerprints.
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56. ▌
    Smiles Parsing Validation · holobiomicslab

    Use when when you have a dataset of molecular structures encoded as SMILES strings that will be processed downstream (e.
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57. ▌
    Sparse Matrix Computation · holobiomicslab

    Use when clustering large collections of high-resolution MS/MS spectra (thousands to millions) and you have already converted spectra to low-dimensional vectors via feature hashing.
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58. ▌
    Spectral Data Exploration · holobiomicslab

    Use when you have completed msFeaST pipeline preprocessing and generated a JSON output file (dashboard_data.
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59. ▌
    Spectral Data Integration · holobiomicslab

    Use when you have three distinct mass spectrometry data sources (quantification table, metadata table, and spectral data from an MS library or reference dataset like omsw_pleurotus_ms2deepscore) and need to combine them into a single JSON output that preserves all three modalities for interactive.
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60. ▌
    Spectral Library Matching · holobiomicslab

    Use when you have one or more MS/MS spectra in .mgf format (or USI identifiers) and need to: (1) identify unknowns by searching against domain-curated reference data; (2) assign Level 2 metabolomics annotations via GNPS library matches; (3) aggregate matches across organism lineages (e.
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61. ▌
    Spectrum Metadata Parsing · holobiomicslab

    Use when a user submits one or more MS/MS spectra (via .mgf file, USI list, or direct upload) and the downstream analysis requires dispatching to a specific domain-specific MASST tool (microbeMASST, plantMASST, tissueMASST, microbiomeMASST, foodMASST, or metadataMASST).
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62. ▌
    Spectrum Query Formatting · holobiomicslab

    Use when you have parsed LC-MS/MS spectral data (precursor m/z, ionization mode, collision energy, and a list of fragment m/z and intensity pairs) and need to submit it to the CSI:FingerID web service for molecular fingerprint prediction as part of a metabolite identification workflow.
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63. ▌
    Survival Data Preparation · holobiomicslab

    Use when when you have clinical survival outcomes (event status and follow-up time) and high-dimensional metabolomic or expression data, and you need to feed them into Cox-PH or Cox-nnet prognosis models.
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64. ▌
    Suspect Database Matching · holobiomicslab

    Use when you have LC-MS peak/feature data, a curated suspect compound database with known m/z, retention time, and fragment ion coordinates, and you observe that traditional peak extraction algorithms have failed to detect ions corresponding to suspected contaminants or chemicals of interest.
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65. ▌
    Thermo Raw Format Parsing · holobiomicslab

    Use when when you have LC-MS data in Thermo .raw format (a proprietary binary output from Thermo mass spectrometers) and need to load it into a 3D LC-MS viewer or extract structured spectral metadata (retention time, m/z values, intensities, scan number, MS level) for visualization or quantitative.
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66. ▌
    Tree To Query Translation · holobiomicslab

    Use when you have a shallow decision tree trained on ChemEcho feature vectors (peak or neutral loss formulas) and need to deploy it as an executable query against tandem mass spectrometry data.
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67. ▌
    Vendor Format Abstraction · holobiomicslab

    Use when you have mass-spectrometry raw data files from multiple vendors (e.g., Thermo, Waters, Bruker, Sciex) and/or mixed standard formats (mzML, mzXML) that must be processed by a single analysis pipeline.
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68. ▌
    Accuracy Metric Computation · holobiomicslab

    Use when after running inference on a trained structure prediction model with one or more input modalities (1H NMR, 13C NMR, or combined), you have generated predicted molecular formulas and connectivity graphs that need to be compared against known ground truth structures.
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69. ▌
    Compound Identifier Mapping · holobiomicslab

    Use when after filtering a peak table to remove mispicked ions, group contaminants, and low-replicability features, you have a curated feature list with m/z, retention time, and MS/MS spectra ready for annotation.
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70. ▌
    JSON Response Serialization · holobiomicslab

    Use when when a backend service receives structured prediction results from an external API (e.g., nmrshiftdb peak predictions) and must return them to a client application via HTTP POST response.
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71. ▌
    Metabolite Score Projection · holobiomicslab

    Use when you have Nightingale Health 1H-NMR metabolomics assay output (metabolite concentrations in a samples × features matrix) and you want to compute a published metabolic risk score or surrogate biomarker (mortality risk, metabolic age, cardiovascular event risk, type-2 diabetes risk, COVID-19.
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72. ▌
    Mixture Spectrum Comparison · holobiomicslab

    Use when you have an observed NMR mixture spectrum and one or more candidate reconstructed spectra (each formed by summing weighted single-compound spectra), and need a continuous, transportable distance metric to score how well the reconstruction approximates the observed mixture.
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73. ▌
    Nmr Peak JSON Serialization · holobiomicslab

    Use when you have proton (1H) and carbon-13 (13C) NMR peak measurements from a molecular sample and need to classify the molecule using the SMART 3 deep learning API. The peaks must be reformatted from their native instrument output into JSON before submission to the /api/smart3/search endpoint.
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74. ▌
    Nmr Spectrum Peak Detection · holobiomicslab

    Use when you have a loaded INADEQUATE NMR spectrum file (after referencing via basic shifting) and need to identify individual peak positions and intensities as input to downstream peak network clustering or metabolite matching.
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75. ▌
    Smiles Structure Annotation · holobiomicslab

    Use when you have LC–QTOF mass spectra from real environmental or biological samples (e.g., wastewater, complex mixtures) and need to assign molecular structures to spectra where traditional library matching fails or reference compounds are unavailable.
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76. ▌
    Spectral Peak Deconvolution · holobiomicslab

    Use when you have a raw 1D NMR spectrum (FID or processed format) from urine, worm, or other biological samples and need to extract peak positions, intensities, and linewidths as a tabular peak list.
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77. ▌
    Atac Seq Peak Annotation · holobiomicslab

    Use when after differential peak analysis (tl.diff_test) has identified peaks that differ in accessibility across cell types or conditions.
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78. ▌
    Bam To Bigwig Conversion · holobiomicslab

    Use when after running TOBIAS ATACorrect to generate bias-corrected signal tracks from aligned ATAC-seq reads. Use this skill when you have corrected cutsite signal (as .
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79. ▌
    Barcode Fragment Mapping · holobiomicslab

    Use when you have a coordinate-sorted BAM file from a single-cell ATAC-seq experiment (especially 10X Genomics platforms) and need to extract per-fragment information including cell barcodes, fragment coordinates, and quality metrics for downstream analysis in SnapATAC2 or compatible tools.
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80. ▌
    Bigwig Signal Processing · holobiomicslab

    Use when after bias correction of ATAC-seq reads (via ATACorrect) when you have a bias-corrected bigWig file and need to measure transcription factor footprint strength within defined accessible regions (peaks, motif sites, or called footprint boundaries).
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81. ▌
    Dmr Detection Bumphunter · holobiomicslab

    Use when you have preprocessed, normalized beta-value matrices from EPIC or 450k methylation arrays with at least two sample groups (case/control, treatment/untreated, or similar contrasts) and seek to identify regions of coordinated differential methylation rather than individual CpG sites.
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82. ▌
    Fragment File Validation · holobiomicslab

    Use when after invoking pp.make_fragment_file to convert a coordinate-sorted BAM file (e.g., from 10X ATAC or standard alignment) into a compressed fragment file.
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83. ▌
    Sparse Matrix Validation · holobiomicslab

    Use when after generating a count matrix from fragment data using pp.add_tile_matrix, pp.make_peak_matrix, or pp.make_gene_matrix in SnapATAC2.
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84. ▌
    API Contract Validation · holobiomicslab

    Use when integrating with an external API (such as TensorFlow Serving) where changes to the response schema could break dependent code, or when model metadata must be extracted and verified before being used in downstream analysis steps.
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85. ▌
    Build System Monitoring · holobiomicslab

    Use when when you need to capture a snapshot of a research software project's health metrics from multiple CI/CD and repository services (Travis CI, Landscape.
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86. ▌
    Ccs Bias Quantification · holobiomicslab

    Use when you have IM-MS lipidomics data acquired on samples spiked with fully labeled U13C lipid standards (e.g., U13C yeast extract), and you need to assess whether systematic CCS deviation exists between your instrument's measured values and the DT CCS N2 reference library for U13C labeled lipids.
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87. ▌
    Data Summary Statistics · holobiomicslab

    Use when you have a curated relational dataset (structure-organism pairs) and need to quantify how structures distribute across a categorical variable (e.g., organism prevalence).
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88. ▌
    Docker Image Management · holobiomicslab

    Use when when you need to confirm that a published Docker image (e.g., hosted on Docker Hub) can be pulled and instantiated successfully, and when the target tool has a defined entry point or CLI interface.
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89. ▌
    Multiquant File Parsing · holobiomicslab

    Use when you have Sciex Multiquant text export files from one or more metabolomics or lipidomics analytical sequences and need to identify and locate QCpool (pooled quality control) samples that should have been injected at regular intervals, or when you must validate that the study design's.
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90. ▌
    Spectral Peak Filtering · holobiomicslab

    Use when you have imported raw mass spectrometry data in formats such as MGF, MSP, mzML, or mzXML and need to clean the spectral data prior to similarity comparisons, metadata validation, or export.
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91. ▌
    Twim Ms Data Processing · holobiomicslab

    Use when you have TWIM-MS data (arrival time and m/z values) from a multi-omic sample and need to: (1) establish a CCS calibration curve from known standards, (2) assign unidentified features to biomolecular classes (e.
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92. ▌
    Workflow Reconstruction · holobiomicslab

    Use when when you have a partially documented or undocumented MS analysis pipeline and need to verify its correctness, trace data provenance through multiple processing stages, integrate tools via unified parameter handling (CTD scheme), or ensure the workflow adheres to community standards for.
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93. ▌
    Analysis Type Selection · holobiomicslab

    Use when preparing to run LipidMatch-4.2 and you need to determine which analysis mode should execute. Specifically: when your input data consists of lipid standards or lipid-rich samples (set Lipid analysis mode); when you are analyzing Tween surfactant-containing samples (set Tween-positive mode);
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94. ▌
    Batch Record Processing · holobiomicslab

    Use when when you have a repository containing hundreds or thousands of structured records (e.g., MassBank records in standardized format) that must be validated for correctness before release or merge.
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95. ▌
    Cdf File Format Parsing · holobiomicslab

    Use when when you have multiple CDF files from mass spectrometry imaging experiments (e.g., root tissue MALDI-MS data) that need to be ingested into Matlab for linear imaging analysis. Trigger: presence of .
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96. ▌
    Command Line Invocation · holobiomicslab

    Use when after completing a BiG-SLiCE clustering analysis and needing to access the pre-calculated BGC and GCF cluster assignments in tabular format for spreadsheet analysis, statistical testing, or integration with other bioinformatics pipelines.
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97. ▌
    Data Frame Augmentation · holobiomicslab

    Use when after assign_hierarchy has added KEGG compound identifiers and hierarchical metadata to your metabolomics count data frame, and you need to link metabolites to their functional orthologs (KO numbers) and gene names for pathway or functional enrichment analysis.
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98. ▌
    Docker Image Deployment · holobiomicslab

    Use when when you have a containerized scientific tool available on Docker Hub (e.
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99. ▌
    Docker Network Creation · holobiomicslab

    Use when when deploying a multi-container application stack using docker-compose where containers need reliable hostname-based service discovery and isolation from the host network.
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100. ▌
     Drugbank Format Parsing · holobiomicslab

     Use when when you have obtained a DrugBank release file (requiring access credentials) and need to extract drug records with standardized fields (names, structures, identifiers, classification) for integration into a metadata enrichment or cleanup workflow that queries multiple drug/natural product.
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