Coding & Dev Tools

holobiomicslab Skill

Use when when you have MS/MS spectra with assigned precursor formulas and need to annotate fragment peaks with their chemical subformulas, but want to avoid the computational overhead of generating full SIRIUS fragmentation trees or do not have access to spectrum databases.

holobiomicslab Skill

Use when you have LC-MS normalized intracellular metabolite abundance data from multiple cell lines (or samples) and need to compute reaction-level propensity scores that account for substrate availability as a predictor of metabolic flux.

holobiomicslab Skill

Use when when you have a set of MS/MS spectra with ground-truth structural similarity labels (Tanimoto scores computed from molecular fingerprints) and need to choose a decision threshold for classifying spectrum pairs as 'chemically related' or 'unrelated'.

holobiomicslab Skill

Use when you have time-resolved direct injection mass spectrometry data (e.

holobiomicslab Skill

Use when you have canonicalized SMILES strings from a chemical database (e.

holobiomicslab Skill

Use when when you have a raw LC-MS peak table imported from vendor software (e.

holobiomicslab Skill

Use when immediately after formula assignment from raw FT-ICR MS peak detection, when you have a peak intensity matrix with assigned molecular formulas and need to remove spurious or low-confidence assignments before calculating thermodynamic indices, determining compound classes, or performing.

holobiomicslab Skill

Use when you have a GNPS-generated classical or feature-based molecular network (in graphml or JSON format) and corresponding MS2LDA or chemical class assignment data, and you need to embed substructural motif identifiers, confidence scores, or chemical class labels as node/edge attributes for.

holobiomicslab Skill

Use when you have a Thermo Fisher Scientific .raw file containing PRM data and need to verify that acquisition of a specific precursor ion (e.g., LGGNEQVTR++ at m/z 487.2567) is happening at regular intervals consistent with your instrument method design.

holobiomicslab Skill

Use when when processing a batch of LC-MS samples in mzML or mzXML format where at least one file has been designated as a quality control (QC) file, extract its TIC or BPC before performing retention time correction.

holobiomicslab Skill

Use when after MZmine feature detection and molecular networking on a single LC-MS/MS DDA sample, when you have a feature table (with retention time, m/z, fragmentation spectra) and sample-level taxonomical metadata, and you want to assign both spectral identity and predicted chemical structure to.

holobiomicslab Skill

Use when after loading multiple LC-MS .mzML files into an MsExperiment object using MsBackendMzR backend, when you have a documented injection sequence (e.

holobiomicslab Skill

Use when you have a set of metabolites or chemical formulas to analyze and want to evaluate how different MS/MS fragmentation strategies (e.g., TopN, exclusion lists, dynamic window selection) would perform without access to real instrument time.

holobiomicslab Skill

Use when when evaluating whether a mass spectrometry analysis platform (such as mzmine) has comprehensive module support across multiple ionisation and separation techniques (LC, GC, IMS, MALDI MS imaging), or when planning a multi-technique MS study and needing to confirm that all intended.

holobiomicslab Skill

Use when after completing all per-sample annotation steps (molecular networking, ISDB/spectral matching, SIRIUS/CSI:FingerID, and compounds metadata enhancement with Wikidata IDs and NPClassifier ontology).

holobiomicslab Skill

Use when you have raw LC-MS data (mzML or equivalent format) from a metabolomics experiment and need to extract a reproducible, quantified feature table with intensity measurements before conducting metabolite identification or statistical analysis.

holobiomicslab Skill

Use when when you have a feature table from Orbitrap LC-MS containing m/z, retention time, and intensity columns, and you need to group individual mass features into putative metabolites that represent the same chemical entity across different ionization states and isotopic compositions.

holobiomicslab Skill

Use when after MS2 annotation and sample alignment have been completed in JPA, when you need to visualize ion chromatograms for quality control, validate feature identities, or export chromatographic evidence for specific metabolic features across multiple samples.

holobiomicslab Skill

Use when after selecting statistically significant features from multi-assay LC-MS metabolomics datasets (e.g., via MB-VIP and permutation testing with p < 0.01).

holobiomicslab Skill

Use when you have paired microbiome (16S rRNA, metagenomic) and metabolomic (LC-MS, GC-MS) abundance tables from the same biosamples, and you want to predict which metabolites are recoverable from microbial composition alone and identify groups of microbes and metabolites with correlated.

holobiomicslab Skill

Use when you have an in-house collection of liquid chromatography spectra and retention time measurements for small molecules, and you want to improve structural identification accuracy by predicting retention times.

holobiomicslab Skill

Use when when you have executed the MultiModalSpectralTransformer architecture on a set of multi-modal spectroscopic inputs (NMR, HSQC, COSY, IR) and obtained predicted molecular structures, and you need to assess prediction accuracy and structural correctness against ground-truth or reference.

holobiomicslab Skill

Use when you have a high-resolution mass spectrum (FT scan) containing a peptide precursor at known charge state with known or suspected stable isotope labeling (e.

holobiomicslab Skill

Use when when you have paired MS/MS spectra from unknown metabolites and a reference database of known metabolites, and you want to rank candidate structures for unknown compounds by their predicted structural similarity rather than exact spectral matching.

holobiomicslab Skill

Use when when you have raw mzML or mzXML mass spectrometry data files that need to be archived or transmitted with minimal storage footprint, and you must verify that the decompressed output exactly reproduces the original input at the byte level.

holobiomicslab Skill

Use when you have measured IM-MS lipidomics data spiked with U13C labeled internal standards and need to assess whether CCS bias remains within acceptable limits for each lipid class-adduct combination.

holobiomicslab Skill

Use when when you have abundance-normalized FT-ICR MS peak data with assigned molecular formulas and need to distinguish between richness (total number of distinct metabolites) and functional diversity (diversity in metabolic potential).

holobiomicslab Skill

Use when you have mass spectrometry data (chromatograms, spectra, peak maps, mobilograms) that you want to visualize interactively using pyOpenMS-viz, and you need to select between bokeh and plotly backends based on execution time and feature parity.

holobiomicslab Skill

Use when you have a peak-abundance matrix from FT-ICR MS (peaks as rows, samples as columns with raw peak intensities) and need to compute abundance-based diversity indices or functional diversity metrics that are sensitive to relative vs. absolute peak heights.

holobiomicslab Skill

Use when you have run an NPP tool (XCMS, MZmine 2, etc.) on mzML files and need to assess whether the alignment stage preserved peak detection fidelity and isotopologue abundance ratios.

holobiomicslab Skill

Use when when you have imported mass spectrometry data in .raw, .d, or mzXML format and need to generate a TIC plot to visualize overall sample ionization intensity as a function of retention time.

holobiomicslab Skill

Use when after initial retention-time-based feature grouping (e.g., ±20 s window) when you need to separate co-eluting features that are chemically distinct. Triggers include: (1) large feature groups (>2–3 members) suspected to contain multiple compounds;

holobiomicslab Skill

Use when when processing multiple LC-MS samples with varying scan numbers or retention-time drift, before constructing composite mass tracks for peak detection.

holobiomicslab Skill

Use when when you have detected LC-MS/MS features (MS1 peaks with MS2 fragmentation spectra) from untargeted metabolomics experiments and seek to organize them into a chemical hierarchy for comparative metabolomic analysis.

holobiomicslab Skill

Use when you have raw or minimally processed tandem MS spectra (in mzML, mgf, or other standard formats) and need to prepare them for spectral matching, library searching, or quantitative analysis.

holobiomicslab Skill

Use when when building a visualization library that must support multiple plotting backends (e.g., matplotlib, bokeh, plotly) and multiple data types (e.g., chromatograms, spectra, peak maps) without duplicating core logic or configuration handling across backend–plot-type combinations.