Use when when reading a binary file format with a magic integer or fixed checksum field at a known offset, and endianness is not explicitly declared in file metadata or header…
Use when when searching for peptide spectra with unknown or open modifications (i.e., any mass shift within a broad tolerance range rather than a fixed set of known modifications).
Use when you have raw LC-MS data in mzML or equivalent binary format from a public repository (MetaboLights, MassIVE) or instrument vendor output, and need to ingest it into…
Use when you have run a metabolomics experiment with incomplete coverage of a reference pathway database (e.g., 10–100% of database metabolites detected), and you plan to use ORA…
Use when when analyzing high-resolution mass spectrometry data from natural-abundance
Use when when you have a processed or annotated MsmsSpectrum object (from USI loading or direct instantiation) and need to generate a figure showing observed peaks, their…
Use when after spreadOut() has converted raw CSV peak data into a structured list, when you have one or more Compound.Name entries from GC-MS that may be ambiguous, non-canonical,…
Use when when you have a list of chemically known compounds and need to validate that an MS processing pipeline (e.g., mzExacto) correctly retrieves their characteristic m/z,…
Use when when you have predicted MS/MS fragments from quantum chemistry calculations on N-Me derived unsaturated sterol structures and need to map each fragment to its precursor…
Use when when you have Thermo Fisher Scientific .raw files from Orbitrap instruments and need to build a quantitative summary of MS1 acquisition intensity dynamics across a…
Use when when performing ChIP-Seq peak calling with MACS3, after duplicate filtering and fragment length prediction (d), to construct the background model that will be compared…
Use when you have a raw GCxGC-MS chromatogram in NetCDF format (.cdf file) and need to import it into R as a 2D-TIC object for preprocessing (smoothing, baseline correction, peak…
Use when you have paired experimental and computational predictions for the same biological property (e.
Use when you have a pre-trained GNN model checkpoint, a test dataset with molecular representations (SMILES, 3D coordinates, adducts) and ground-truth labels, and need to quantify…
Use when training embeddings from MS/MS spectra and you need to simultaneously enforce: (1) discrimination between spectra with different structural properties via contrastive…
Use when you have a chemical substrate and need to predict its biotransformation
Use when you have executed batch searches against one or more domain-specific MASST tools and received multiple output files (_microbe.html, _plant.html, _tissue.html,…
Use when when you have raw untargeted LC-MS metabolomics data and need to detect low-quality or mis-integrated peaks in an XCMS-processed xcmsSet object before performing…
Use when you have created a GNPS molecular network (either classical or feature-based) and have computed MS2LDA motif assignments (probability and overlap scores) for the same…
Use when you have chemical entity records scattered across two or more public repositories (e.g., HMDB, ChEMBL, PubChem, KEGG) and need a single authoritative, deduplicated…
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…
Use when you have raw gas or liquid chromatography–mass spectrometry data (in NetCDF or mzML format) and need to detect features, align them across samples by retention time and…
Use when when you have extracted mass tracks (EICs) from individual LC-MS samples and need to establish reliable landmarks for subsequent pairwise or global alignment across a…
Use when you have Thermo Orbitrap .raw files and need to access raw spectral data (individual MS1 or MS2 scans, base-peak values, chromatogram traces, retention times, or…
Use when you have untargeted metabolomics data with unknown metabolite structures and need to generate plausible candidate products by systematically applying known enzymatic or…
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…
Use when when deploying a multi-service microarchitecture (such as MAGMa''s four distinct subprojects: magmaweb, joblauncher, job, and pubchem) via Docker Compose and you need to…
Use when when a metabolite feature has been assigned a top-rank lipid annotation (e.g., LPC(14:0)) but you need to assess whether related lipid species containing the same fatty…
Use when when preparing heterogeneous column-metadata inputs for a graph transformer model that operates on molecular graphs.
Use when when you have completed an initial ModiFinder analysis on a compound pair (known compound + modified analog with unknown structure), and you subsequently acquire or…
Use when you have generated or obtained a two-dimensional mass-spectrometry intensity matrix (m/z × retention time scan points) with simulated or experimental peak shapes, noise,…
Use when your TWIM-MS dataset contains ions with multiple charge states (e.g., +1, +2, +3 for the same molecular species) and you need CCS values that correctly account for the…
Use when you are receiving molecular structures from external sources (COCONUT database, ZINC database, user-provided chemical data) in varying formats (SMILES strings, InChI…
Use when during MS/MS spectral preprocessing when converting raw spectra from .mgf, .msp, or .mzML formats into a bag-of-fragments corpus for LDA modeling.
Use when when processing mass spectrometry spectral records from a database where critical fields (e.g., adduct annotation) are absent or null, and you have a secondary field…
Use when after denoising MS/MS spectra at multiple frequency thresholds and matching each thresholded spectrum against a -matching reference spectrum.
Use when when a Python package provides optional support for specialized data formats or functionality (e.
Use when you have mass spectrometry data loaded as a Pandas DataFrame with retention time and intensity columns, and you need to visualize the overall or mass-trace-specific…
Use when after performing peak detection on centroided .mzML LC-MS data with screening_mode=FALSE in TARDIS.
Use when when performing transcript- or gene-level differential expression analysis and your quantification tool (Salmon, Sailfish, or kallisto) has produced Gibbs sample or…
Use when you have intensity measurements (peak features, protein intensities, or gene expression values) with compound or gene annotations (KEGG IDs, ChEBI IDs, UniProt IDs, or…
Use when immediately after parsing mzML files into (m/z, scan_number, intensity) tuples when you need to build mass tracks from raw MS1 spectra.
Use when you have a collection of MS/MS spectra (≥2 spectra) and wish to identify fragmentation signatures common to subsets of those spectra.
Use when when you have (1) transcriptomics data and a metabolic network model with GPR rules to compute RAS scores; (2) constraint-based model predictions (RPS from optGpSampler…
Use when after sample alignment step in untargeted LC-MS workflows, particularly when processing multi-sample cohorts with QC samples interspersed throughout the sequence.
Use when you have preprocessed 1D ¹H and/or ¹³C NMR spectra from an unknown organic compound with ≤19 heavy atoms, and you need to recover its molecular structure (both formula…
Use when you have a precomputed expected contact frequency table (TSV with columns: dist_bp, contact_frequency, n_valid) derived from cooler Hi-C matrices and need to generate a…
Use when when you have a scientific software tool (e.g., Met-ID) that is architected to support plugins or configuration-driven modules, and you need to register and apply a novel…
Use when annotating matrix-related signals in MSI datasets where chemical formulas or spatial distributions alone are ambiguous, or when multiple ions share nominal m/z values…
Use when you have: (1) a trained IOKR model mapping from spectrum kernels to molecular fingerprints, (2) MS2 spectra from your sample, (3) a set of candidate BGCs with known or…
Use when when you have mass-spectrometry data (m/z and intensity pairs or spectral matrices) paired with ground-truth molecular fingerprints or InChIKeys, and you need to learn a…
Use when when you have a feature intensity table (samples × compounds) from targeted or non-targeted metabolomics and need to prepare it for statistical modeling or multivariate…
Use when you have intracellular metabolomics concentration measurements across multiple cell lines or conditions, a stoichiometric metabolic network model with reaction-metabolite…
Use when you have a pre-trained GNN model for CCS prediction and need to verify that it generalizes to test data that was held out during training.
Use when after labeling a representative subset of peaks (typically 10–20 pooled samples with corresponding feature tables) and before neural network training, when you need to…
Use when you have a normalized gene expression matrix (log2-quantile normalized, filtered to high-variance genes) and a collection of annotated gene sets (e.g., Reactome, MSigDB…
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,…
Use when after constructing a network graph where nodes represent Mass2Motifs (or spectra) and edges encode pairwise spectral similarity scores, and you need to export the network…
Use when when testing associations between metabolic features (from NMR or MS) and a phenotype of interest (e.g., BMI, disease status) in a cohort where age, gender, or clinical…
Use when when you have an unknown mass spectrum (query spectrum) and need to search it against a reference database of billions of spectra to find matching or structurally related…