Integrations & APIs

holobiomicslab Skill

Use when when you need to expose a multi-step spectral processing workflow (parse → extract → render → annotate → compress) as a web service endpoint that accepts jcamp/RAW/mzML spectral files and must return coordinated output artifacts (modified JCAMP files, peak tables, and PNG images) in a.

holobiomicslab Skill

Use when you have mwTab-formatted files from the Metabolomics Workbench containing MS or NMR experimental metadata and data blocks that need to be converted to JSON for integration with REST APIs, web applications, or downstream tools that expect JSON input.

holobiomicslab Skill

Use when you have raw mass spectrometry data in mzML or mzXML format and need to compress it using a format-agnostic compressor that expects a standardized spectral data contract.

holobiomicslab Skill

Use when when building or maintaining a local natural-product reference database that requires current Wikidata entries, or when preparing metadata for mass-spectrometry queries that need enriched compound annotations (e.g., alternative names, chemical classifications, source organisms).

holobiomicslab Skill

Use when a QC check fails during an active LC-MS instrument run and you need to immediately notify configured users (via Slack channel or email address) of the failure event, including timestamp, check type, and severity metadata.

holobiomicslab Skill

Use when when you have a functional R package with core statistical or computational logic that needs to be made accessible to non-R users, or when you want to streamline a multi-step analytical workflow (e.

holobiomicslab Skill

Use when after completing Part 4 (Identification of ISF Features) in the ISFrag workflow, when you have an ISFrag analysis results object containing identified ISF features and need to save them as a portable, tabular file for external analysis, reporting, or integration with other metabolomics.

holobiomicslab Skill

Use when you have NMR peak data (1H and 13C chemical shift values) that must be submitted to a remote DeepSAT SMART 3 classification API for structural prediction, and you need to format the data correctly, validate the endpoint schema, and parse the response to extract predictions and confidence.

holobiomicslab Skill

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.

holobiomicslab Skill

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.

holobiomicslab Skill

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.

holobiomicslab Skill

Use when you have independent metabolomic GWAS results (metabolite p-values, effect sizes, metabolite IDs) and separate meta-genome GWAS results (variant p-values, effect sizes, genomic variant IDs) from similar diseases or phenotypes, and you want to discover novel metabolite–gene associations and.

holobiomicslab Skill

Use when when you have raw chemical structures in diverse input formats (SMILES, SDF, or other molecular representations) from multiple sources and need to produce a uniform, canonicalized representation before molecular descriptor calculation, fingerprinting, or retention time modeling.

holobiomicslab Skill

Use when you have identified a published method (e.g., MIST-CF for chemical formula ranking from mass spectra) whose source code and trained weights are available in a public repository, and you need to apply that method to new experimental data (e.

holobiomicslab Skill

Use when when you have a parsed mass spectrum (precursor m/z, ionization mode, collision energy, and fragment peak list as m/z–intensity pairs) and need to obtain molecular fingerprint predictions, de-novo candidate structures, or chemical class annotations without maintaining local neural network.

holobiomicslab Skill

Use when when a web service must accept spectroscopic measurements (NMR peaks, IR/MS metadata) submitted as form-encoded POST parameters from a client, and those parameters need to be validated, reformatted into an external API query format, or passed to a downstream predictor service.

holobiomicslab Skill

Use when when you have developed or obtained a new Python package that encapsulates domain-specific computational logic (e.

holobiomicslab Skill

Use when your input is a raw query string containing a chemical compound identifier and structural representation (e.g. tab-delimited compound ID + structure), and you need to submit it to the ClassyFire API for automatic structure-based classification.

holobiomicslab Skill

Use when when you have generated a feature abundance matrix from mzrtsim() peak list simulation with known sample-level attributes (condition assignments, batch labels, sample identifiers) and need to package this into a SummarizedExperiment object for Bioconductor-compatible analysis pipelines.

holobiomicslab Skill

Use when you have custom lipid entries (e.g., synthetic lipids, rare natural variants, or isotopically labeled standards) not covered by LipidMatch's default in-silico library, and you want to include them as matching candidates in your UHPLC-HRMS/MS fragment m/z matching workflow without modifying.

holobiomicslab Skill

Use when you have a Galaxy installation (specifically Galaxy Master branch commit c429777c93680dcee449fe410f5360afbe673758 or compatible) and need to add metabolomics analysis capabilities including tools for XCMS integration, mass spectrometry file reading (via MSFileReader), and metabolite.

holobiomicslab Skill

Use when when you have matched transcriptomics (RNA-seq read counts), intracellular metabolomics (LC-MS abundance data), and extracellular flux measurements (YSI bioanalyzer or similar) from multiple biological samples or cell lines, and you need to determine whether differences in metabolic enzyme.

holobiomicslab Skill

Use when a paired omics project record contains a genome identifier (e.g., GenBank accession) but lacks the corresponding organism name field, and you need to populate that metadata field to enable full text search, sample tracking, or project validation before archival to Zenodo.

holobiomicslab Skill

Use when after implementing or modifying a cross-language integration layer that wraps Python mass spectrometry functions (e.g., spectral matching, peak detection, normalization from matchms or spectrum_utils) as R-callable functions within Spectra workflows.

holobiomicslab Skill

Use when when a QC check fails during an active LC-MS run and configured email notification targets exist in the system. Use this skill to ensure that QC failures are communicated to stakeholders immediately, complementing Slack-based alerts for users who prefer or require email notification.

holobiomicslab Skill

Use when when you have Thermo Fisher RAW mass spectrometry files and need to extract mass-to-charge ratios, intensities, scan metadata, and peak lists within a Python script or notebook for downstream computational analysis, and you require programmatic control over extraction parameters rather.

holobiomicslab Skill

Use when when you have downloaded a GNPS molecular networking archive (GNPS1 or GNPS2 workflow output) and need to reconstruct spectral records for integration with genomic data (BGCs, antiSMASH results) or for computing molecular family links and spectral similarity scores.

holobiomicslab Skill

Use when when you have a multi-step computational workflow (e.g., peak detection, filtering, manual review) implemented in R and need to expose it to end-users who lack R expertise.

holobiomicslab Skill

Use when when you have multiple mass spectrometry data formats (mzML, mzXML, or others) that must be ingested into a single format-agnostic processing engine (e.g., mspack compression), and you need to avoid replicating the core logic for each format.

holobiomicslab Skill

Use when you have collected or parsed 1H and 13C NMR peak data (chemical shift values and intensities) and need to submit it to the SMART 3 /api/smart3/search endpoint or similar TensorFlow Serving-backed molecular classification system that expects peaks as JSON rather than raw spectroscopic files.

holobiomicslab Skill

Use when you have a SMILES string or batch of SMILES strings representing chemical structures and need to obtain NP Classifier predictions programmatically.

holobiomicslab Skill

Use when you have a collection of MassBank records (in plain-text or structured format) that need to be systematically validated for conformance to MassBank format specification—particularly in a continuous integration context where validation must run on every commit or pull request to maintain.

holobiomicslab Skill

Use when you have a repository of structured records (e.g., mass spectrometry data, metadata, or domain-specific formats) and need to enforce validation rules systematically across all records.

holobiomicslab Skill

Use when you have untargeted metabolomics data from multiple MS instruments (e.

holobiomicslab Skill

Use when you have aligned and baseline-corrected GC-IMS data with detected and clustered peaks, and you want to extract peak intensities using a consistent integration window.

holobiomicslab Skill

Use when when you have a GNPS molecular network (graphml or cytoscape format) and wish to annotate it with chemical class labels or MS2LDA-derived mass2motifs to highlight shared structural features or chemical families across spectral clusters.