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HolobiomicsLab

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1. ▌
   Feature Group Refinement Multicriteria 2 · holobiomicslab

   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;
   0 installs
2. ▌
   Gcxgc Chromatogram Object Manipulation 2 · holobiomicslab

   Use when you have raw GCxGC-MS data in NetCDF format that contains instrumental and chemical noise (baseline drift, high-frequency signal artifacts) and you need to prepare multiple preprocessed chromatogram objects for downstream multiway PCA or biomarker discovery.
   0 installs
3. ▌
   Image Based Feature Extraction Ms Maps 3 · holobiomicslab

   Use when you have a two-dimensional MS map (m/z vs retention time) from GC–MS or LC–MS data and need to discriminate analytes and identify marker features without false positives from peak picking; particularly useful for untargeted metabolomics at ppb sensitivity (e.
   0 installs
4. ▌
   Lc Ms Feature Extraction And Alignment 2 · holobiomicslab

   Use when you have centroid mzML files from LC-MS experiments (converted from Thermo .raw or other vendor formats) and need to identify and quantify individual chemical features across multiple samples.
   0 installs
5. ▌
   Lc Ms Feature Grouping And Compounding 2 · holobiomicslab

   Use when after chromatographic peak detection on preprocessed LC-MS data, when you have hundreds or thousands of individual m/z × retention-time peaks and need to associate them into biologically meaningful feature groups.
   0 installs
6. ▌
   Mass Spectral Metadata Standardization 2 · holobiomicslab

   Use when you have acquired EI or MS/MS spectral libraries from multiple public sources (NIST, RIKEN, MoNA, SWGDRUG, GNPS) with inconsistent metadata field layouts, missing or misplaced SMILES entries, undocumented retention indices, or mixed polarity modes, and you need to merge them into a single.
   0 installs
7. ▌
   Metabolite Annotation Ensemble Ranking 2 · holobiomicslab

   Use when you have ESI/LC-MS test spectra requiring candidate metabolite ranking, pre-trained MLP (NEIMS) and GNN baseline models are available or can be trained, you seek quantified improvement over single-model average rank performance (baseline MLP shows ~339 average rank), and your evaluation.
   0 installs
8. ▌
   Metabolite Annotation Mlp Gnn Ensemble 2 · holobiomicslab

   Use when you have ESI/LC-MS test spectra requiring metabolite annotation and need to compare ensemble-based neural network predictions (ESP) against a baseline MLP model to quantify performance gains.
   0 installs
9. ▌
   Metabolite Rank Performance Evaluation 2 · holobiomicslab

   Use when after training an ensemble model (MLP, GNN, or ESP) on spectral data, use this skill to measure performance on test spectra where ground-truth metabolite identities are known. Essential for comparing model variants (e.
   0 installs
10. ▌
    Metabolite Reference Library Filtering 2 · holobiomicslab

    Use when you have defined one or more proton NMR spectral regions-of-interest (ROIs) with lower and upper chemical-shift bounds (in ppm) from an experimental NMR spectrum of a biological sample, and you need to identify which metabolites in a reference database (HMDB) have published 1H NMR shifts.
    0 installs
11. ▌
    Neutral Loss Annotation Interpretation 3 · holobiomicslab

    Use when when building Word2Vec or embedding-based spectral similarity models where you need to capture fragmentation patterns beyond individual peak positions.
    0 installs
12. ▌
    Peak Filtering And Preprocessing Lc Ms 2 · holobiomicslab

    Use when you have raw LC-MS/MS spectra from vendor instruments (mzML, mzXML, MGF, or MSP format) with variable peak quality and intensity distributions, and you plan to perform library matching, molecular networking, or spectral similarity comparison.
    0 installs
13. ▌
    Retention Time Prediction Optimization 3 · holobiomicslab

    Use when when you have a retention-time dataset (e.g., SMRT or Eawag_XBridgeC18_364) in .xlsx format and need to train or adapt a graph neural network model to predict chromatographic retention times for new compounds.
    0 installs
14. ▌
    Unsupervised Pattern Discovery Spectra 2 · holobiomicslab

    Use when when you have preprocessed mass spectral data (normalized peak intensities or binned m/z representations) and need to discover latent spectral patterns to enhance neural network predictors without labeled spectral classes.
    1 install
15. ▌
    Derivatizing Matrix Configuration 2 · holobiomicslab

    Use when you have a derivatizing matrix (e.g., TAHS or other publicly documented reagent) with known composition and ionization behavior that you want to use in Met-ID for metabolite annotation, and the matrix is not yet configured in your Met-ID installation.
    0 installs
16. ▌
    M Z Metabolite Annotation Mapping 3 · holobiomicslab

    Use when when you have a spatial metabolomics or LC-MS dataset with detected m/z features (as a feature matrix or SpaMTP Seurat object) and need to assign metabolite identities. Specifically: you have observed m/z values, you know the ionization polarity and expected adduct form (e.
    0 installs
17. ▌
    Msi Feature Metadata Preservation 3 · holobiomicslab

    Use when you are converting a processed Cardinal MSImagingExperiment object (containing normalized peaks, optional spatial shrunken centroids segmentation, and feature m/z annotations) into a Seurat object for downstream pathway analysis, differential metabolite expression, or integrative.
    0 installs
18. ▌
    Ppm Tolerance Scoring And Ranking 3 · holobiomicslab

    Use when you have extracted a list of candidate molecular formulae for a given m/z value and need to rank them by plausibility.
    0 installs
19. ▌
    Accurate Mass Database Search 2 · holobiomicslab

    Use when after peak detection and MS1 feature extraction from FIA-MS, GC-MS, LC-MS(/MS), or CE-MS data, when you need to identify unknown metabolites by matching observed m/z values to a reference database and want to recover HMDB identifiers, molecular formulas, and structural annotations for.
    0 installs
20. ▌
    Gradient Performance Encoding 3 · holobiomicslab

    Use when when you have extracted retention times from the top detected MS1 features in a LC-MS run and need to evaluate whether the gradient spreads those compounds efficiently across the available chromatographic time window—particularly during iterative gradient optimization where you need a.
    0 installs
21. ▌
    Algorithm Parameter Comparison Analysis 2 · holobiomicslab

    Use when when you need to evaluate how a specific algorithm parameter (such as SearchMolecularFormulas first_hit mode) affects the quantity and quality of molecular formula assignments on a given spectrum or dataset.
    0 installs
22. ▌
    Data Normalization In Mass Spectrometry 3 · holobiomicslab

    Use when you have raw or partially processed metabolomics data (mzML/mzXML format) from LC-MS or GC-MS runs and need to apply standardized feature detection, alignment, and intensity normalization as part of a reproducible workflow.
    0 installs
23. ▌
    Electron Ionization Spectral Comparison 2 · holobiomicslab

    Use when you have a query electron ionization (EI) mass spectrum in msp format and wish to identify it by matching against a reference spectral library. Apply this skill when you need ranked similarity scores between the query and each library entry to prioritize candidate identifications.
    0 installs
24. ▌
    Ccs Prediction Model Application 3 · holobiomicslab

    Use when you have structural input data (SMILES or molecular geometry files) for N-Me derived unsaturated sterol lipids and need to generate a predicted CCS dataset indexed by lipid identifier and structural isomer class.
    0 installs
25. ▌
    Fragment Ion Difference Counting 2 · holobiomicslab

    Use when when preparing tandem MS/MS data for spectral alignment and similarity comparison, particularly when you have loaded raw fragmentation spectra and need to extract and quantify mass difference patterns that capture the fragmentation process.
    0 installs
26. ▌
    Gc Ims Peak Alignment Evaluation 2 · holobiomicslab

    Use when after peak detection in GC-IMS preprocessing, when you need to assess whether detected peaks from multiple samples align to the same chemical entities (clusters) using hierarchical clustering.
    0 installs
27. ▌
    Ion Mobility Dimension Detection 2 · holobiomicslab

    Use when when processing raw mass spectrometry data files of unknown or mixed provenance, and you need to automatically route IMS inputs to their corresponding analysis pipeline.
    0 installs
28. ▌
    Marker Ion Ranking And Filtering 3 · holobiomicslab

    Use when you have extracted latent low-dimensional peak features from imaging mass spectrometry (IMS) data using a graph-attention autoencoder and need to identify a ranked subset of marker ions that represent spatial metabolomic patterns.
    0 installs
29. ▌
    Peak Deconvolution Preprocessing 3 · holobiomicslab

    Use when you have raw IM-MS data in Agilent MassHunter (.d) or UIMF format from drift tube (DT) or SLIM instruments, and you intend to perform HRdm demultiplexing or peak deconvolution to resolve co-eluting or structurally similar ions.
    0 installs
30. ▌
    Spectral Intensity Normalization 2 · holobiomicslab

    Use when after removing precursor and noise peaks from an MsmsSpectrum object when the spectrum contains peaks with highly variable intensities (e.g., one or two dominant peaks with many weaker fragments).
    0 installs
31. ▌
    Analyte Discrimination Machine Learning 3 · holobiomicslab

    Use when you have raw chromatography–mass spectrometry data (GC-MS or LC-MS) in 2D m/z–retention time format and need to identify and discriminate multiple analytes while avoiding false peak detections inherent in conventional peak picking.
    0 installs
32. ▌
    Candidate Formula Ranking By Mass Error 2 · holobiomicslab

    Use when after querying a formula database (KEGG, PubChem, or user-supplied) with neutral mass values derived from observed m/z peaks and adduct transformations, when multiple candidate formulae fall within the configured mass tolerance window (ppm or Da) and you need to rank them by likelihood.
    0 installs
33. ▌
    Chromatographic Peak Overlap Resolution 2 · holobiomicslab

    Use when analyzing GC-MS data containing overlapping chromatographic peaks—a common scenario in untargeted metabolomics and environmental screening where sample complexity or chromatographic resolution limitations cause co-elution of structurally similar or temporally proximate compounds.
    0 installs
34. ▌
    Mass Spectrometry Spectrum Tokenization 3 · holobiomicslab

    Use when you have pre-processed MS/MS spectra and need to prepare them for word-embedding-based similarity methods (e.g., Spec2Vec).
    0 installs
35. ▌
    Mass Spectrum Extraction And Formatting 2 · holobiomicslab

    Use when you have raw GC-MS data in netCDF or vendor-specific binary format and need to separate co-eluting compounds and extract clean mass spectra for each individual chemical component prior to molecular networking, spectral matching, or metabolite identification workflows.
    0 installs
36. ▌
    Ms Spectra Extraction And Preprocessing 3 · holobiomicslab

    Use when you have raw LC-MS/MS data in mzML or mzXML format and need to: (1) identify the top-abundance MS1 signals in an LC run, (2) compute a single scalar metric (separation efficiency) that summarizes how well compounds are resolved across the chromatogram, and (3) feed that metric into a.
    0 installs
37. ▌
    Neutral Loss Calculation From Precursor 3 · holobiomicslab

    Use when when converting MS/MS spectra into spectral documents for Spec2Vec embedding, and you want to capture chemical relationships implicit in the fragmentation pattern (e.g., loss of water, ammonia, or CO2) that may correlate with structural similarity. Use this when the neutral loss range (5.
    0 installs
38. ▌
    Parameter Driven Preprocessing Pipeline 2 · holobiomicslab

    Use when you have converted mass spectrometry data in mzXML or mzML format and need to extract metabolic features via region-of-interest (ROI) search followed by preprocessing and augmentation.
    0 installs
39. ▌
    Retention Time Alignment Across Batches 3 · holobiomicslab

    Use when you have extracted peaks from multiple LC/HRMS batches (n > 500 samples across different analytical runs or days) and observe systematic retention time drift or offset between batches, preventing reliable cross-batch peak matching on m/z and RT alone.
    0 installs
40. ▌
    Signal Acquisition Error Quantification 3 · holobiomicslab

    Use when you have processed the same GC–MS dataset (m/z vs retention time) through two independent signal acquisition pipelines and need to compute and compare their detection accuracy. Use this skill when one method (e.
    0 installs
41. ▌
    Spectral Similarity Scoring Computation 3 · holobiomicslab

    Use when you have a query spectrum (or set of query spectra) and need to rank candidate library spectra by their likelihood of sharing the same chemical structure.
    0 installs
42. ▌
    Formula Network Extraction From Mz 3 · holobiomicslab

    Use when you have an observed m/z value from spatially-resolved mass spectrometry imaging and need to assign one or more plausible molecular formulae with confidence metrics.
    0 installs
43. ▌
    Fragmentation Pattern Similarity Scoring 3 · holobiomicslab

    Use when after feature detection and alignment have produced a feature table with MS/MS spectra, and you have access to a reference spectral database (e.g., xenobiotic reaction libraries or public databases).
    0 installs
44. ▌
    Mass Spectrometry Data Loading 2 · holobiomicslab

    Use when you have raw MS data files from supported instruments (Agilent, Thermo, Bruker, or mzML format) and need to ingest them into IonToolPack for visualization, quality control, targeted extraction, or spectral library matching.
    0 installs
45. ▌
    Mass Spectrometry Data Parsing 4 · holobiomicslab

    Use when you have received raw or vendor-converted centroid mzML files from LC-MS, GC-MS, or DI-MS platforms and need to extract MS1 spectra before building mass tracks, performing peak detection, or constructing composite feature maps.
    0 installs
46. ▌
    Multi Sample Cohort Assessment 2 · holobiomicslab

    Use when when you have MS1 mass spectrometry data from multiple samples (a cohort) acquired across an instrument run or batch, and you need to identify which samples deviate from cohort norms or which ion targets show anomalous behavior.
    0 installs
47. ▌
    Target List Coordinate Mapping 2 · holobiomicslab

    Use when you have a CSV-formatted target list with m/z, retention time, or ion mobility identifiers and need to locate and extract peak abundances from raw MS data files (Agilent .d, Thermo .raw, Bruker .d, mzML) acquired across LC-MS, LC-IMS-MS, DDA, DIA, or direct infusion modes.
    0 installs
48. ▌
    Xcms Data Import Preprocessing 2 · holobiomicslab

    Use when you have raw LC-MS or GC-MS data files from a mass spectrometer (in mzML, NetCDF, or mzXML format) and need to detect chromatographic peaks, correct m/z bias via mass calibration (e.
    0 installs
49. ▌
    Ccs Calibration Tunemix Execution 2 · holobiomicslab

    Use when you have positive-mode tune mix reference data (e.g., example_tune_pos.h5) with known CCS values spanning a wide m/z range (e.g., 118.086–1522 m/z) and need to establish a CCS calibration model to convert experimental drift times or collision cross sections for downstream analysis.
    0 installs
50. ▌
    Metabolomics Data Format Handling 2 · holobiomicslab

    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 MetaboAnalystR 4.0 for unified LC-MS1 feature detection and MS/MS spectra processing.
    0 installs
51. ▌
    Ms Instrument Type Classification 2 · holobiomicslab

    Use when when evaluating or designing a mass spectrometry data analysis platform, and you need to verify that every supported separation/ionisation technique (LC, GC, IMS, MS Imaging) is covered by at least one processing module.
    0 installs
52. ▌
    Msi Metadata Curation And Storage 2 · holobiomicslab

    Use when after generating a 3D pixel array (shape n+1, y, x) from raw line-scan MSI data via MSIGen's get_image_data() call, curate and validate the accompanying JSON metadata file before visualization or downstream analysis.
    0 installs
53. ▌
    Multi Instrument Data Integration 2 · holobiomicslab

    Use when you have DIA mass spectrometry raw files from multiple instrument types (timsTOF, TripleTOF, Orbitrap) in their native formats (.raw, .d, .
    0 installs
54. ▌
    Proteomics Data Format Conversion 2 · holobiomicslab

    Use when you have vendor raw files (e.g., .raw from Thermo, .d from Agilent, .wiff2 from Sciex) that need to be converted to a standard format for analysis pipelines, data sharing, or when you require the high compression rates and fast decoding provided by Aird format.
    0 installs
55. ▌
    Transformation Product Prediction 2 · holobiomicslab

    Use when after parent chemical suspects have been identified in a non-target screening workflow, use this skill when you need to screen for downstream products formed by chemical or biological transformation.
    0 installs
56. ▌
    Mass Spectrometry Data Format Conversion 3 · holobiomicslab

    Use when you have mass spectral libraries from multiple sources (e.g., NIST EI, RIKEN MS2, MoNA GC-MS or LC-MS/MS, GNPS mgf) that need to be consolidated for use in MS-DIAL, or you have a single library with incomplete or malformed metadata (e.
    0 installs
57. ▌
    Mass Spectrometry Data Quality Filtering 2 · holobiomicslab

    Use when you have generated a complete feature table from mzML files (e.g., Asari 'full' feature table) and need to curate it for downstream analysis.
    0 installs
58. ▌
    Mass Spectrometry File Format Conversion 3 · holobiomicslab

    Use when you have raw MS data files in vendor-native format (.raw, .d, .ms) from CE-MS or LC-MS instruments and need to process them through AriumMS or other open-source metabolomics pipelines that require standardized XML-based interchange formats.
    0 installs
59. ▌
    Metabolomic Feature Extraction From Mzml 2 · holobiomicslab

    Use when you have centroid mzML files from LC-MS acquisitions and need to detect, group, and quantify metabolomic features for a PCPFM experiment. Use it as the first feature-level processing step after file format conversion from raw instrument files (e.g., .raw to mzML via ThermoRawFileParser).
    0 installs
60. ▌
    Noise Smoothing Chromatographic Signals 2 · holobiomicslab

    Use when when you have raw LC-HRMS profile-mode data (rt × mz intensity matrices) and need to detect chromatographic peaks using gradient-descent or local-maxima algorithms.
    0 installs
61. ▌
    Python Binding Generation With Nanobind 2 · holobiomicslab

    Use when when you have a C++ library (such as OpenMS) with nanobind binding specifications in a designated bindings directory and need to create a Python module that exposes C++ classes, functions, and data types to Python code.
    0 installs
62. ▌
    Spectrum Metadata Extraction Validation 2 · holobiomicslab

    Use when when ingesting heterogeneous MS spectral data from multiple open-access libraries (OMS libraries) where metadata completeness and correctness are uncertain.
    2 installs
63. ▌
    Cardinal Object Structure Understanding 2 · holobiomicslab

    Use when when you have loaded a raw or processed Cardinal MSImagingExperiment object from MS imaging data and need to (1) extract spectral intensities and m/z feature information for conversion to other formats (e.g., Seurat), (2) verify that normalization or spatial segmentation (e.
    2 installs
64. ▌
    Cell Type Protein Profiling Integration 2 · holobiomicslab

    Use when you have co-registered IMC (protein imaging mass cytometry) and SIMS (secondary ion mass spectrometry for metabolites) data from the same tissue regions, cell segmentation masks, and need to assign cell types based on protein expression patterns, then overlay those assignments onto.
    0 installs
65. ▌
    M Z Annotation Reduction Quantification 2 · holobiomicslab

    Use when you have spatial metabolomics data with semi-colon-delimited multi-isomer annotations (e.g., 'all_IsomerNames' column in SpaMTP Seurat objects) and you want to quantify the benefit of RefineLipids simplification with lipid_info='simple' parameter.
    2 installs
66. ▌
    Msi Intensity Matrix Isotope Correction 2 · holobiomicslab

    Use when you have loaded a feature-by-pixel intensity matrix (HDF5 format following Cardinal::HDF5 layout) from imzML MSI data in positive ion mode and you have identified paired [M+H]+ and [M+Na]+ features for the same neutral lipid species (differing by ~22 Da in m/z).
    0 installs
67. ▌
    Spatial Segmentation Shrunken Centroids 2 · holobiomicslab

    Use when apply SSC when you have preprocessed and normalized MS imaging data (e.g., after TIC normalization and peak processing) and need to discover spatially distinct metabolite regions without prior tissue annotation.
    0 installs
68. ▌
    Spectral Vector Normalization By Intensity 2 · holobiomicslab

    Use when when converting pre-processed MS/MS spectra into fixed-length vector representations using Word2Vec embeddings for Spec2Vec similarity scoring. Specifically, apply this skill after you have represented individual peaks and neutral losses as words ('peak@xxx.xx', 'loss@xxx.
    1 install
69. ▌
    Chromatographic Window Coverage Assessment 2 · holobiomicslab

    Use when after extracting retention times from top MS1 features detected in an LC-MS run, and when you need to evaluate whether a given gradient time range (e.g., 0–30 minutes) is being used efficiently to separate compounds. Apply this skill as the objective function in gradient optimization (e.
    0 installs
70. ▌
    Classification Algorithm Tuning Validation 2 · holobiomicslab

    Use when you have labeled training data (e.g., pqm_development with 500 peaks and 89 samples) and need to select which of multiple classification algorithms (e.g., AdaBoost, Random Forest, SVM) and their hyperparameters (e.
    2 installs
71. ▌
    Compound Identification Ranking Evaluation 2 · holobiomicslab

    Use when after training a FlavorFormer model end-to-end with weighted loss on 1H NMR spectra and compound labels, apply this skill to a held-out test set to measure compound identification accuracy and ranking quality.
    0 installs
72. ▌
    Descriptor Fingerprint Feature Engineering 2 · holobiomicslab

    Use when use when the workflow requires descriptor-fingerprint-feature-engineering.
    2 installs
73. ▌
    Filter Criteria Composition And Validation 2 · holobiomicslab

    Use when you are preparing to reuse public tandem MS data from MassIVE via ReDU and need to partition files by sample metadata (e.g., organism, tissue type, extraction method, ionization source, pre-MS separation) into groups for co-analysis.
    2 installs
74. ▌
    Gc Ms Data Preprocessing And Normalization 2 · holobiomicslab

    Use when you have raw GC-MS data (aroma, breath, or other volatile analyte samples) in NetCDF or vendor-native format and need to identify multivariate chemo-/biomarker features without conventional peak picking.
    2 installs
75. ▌
    Graph Neural Network Architecture Assembly 2 · holobiomicslab

    Use when when you have: (1) a collection of molecules represented as molecular graphs (nodes=atoms, edges=bonds with chirality/order attributes); (2) structured metadata describing experimental conditions (e.
    0 installs
76. ▌
    Group Wise Chemical Enrichment Calculation 2 · holobiomicslab

    Use when when comparing GNPS chemical annotations across two or more groups of samples (defined by ReDU sample-information categories such as sample type, extraction method, or ionization source) where the groups contain different numbers of files.
    0 installs
77. ▌
    High Quality Spectral Library Benchmarking 2 · holobiomicslab

    Use when you have a pre-trained MS/MS spectral embedding model and need to validate that it achieves strong and consistent retrieval performance on curated spectral libraries that represent real-world data quality standards.
    2 installs
78. ▌
    Interactive Spectral Visualization Emperor 2 · holobiomicslab

    Use when when you have computed PCA coordinates from chemical annotation matrices (e.
    1 install
79. ▌
    Ionization Mode And Column Mode Separation 2 · holobiomicslab

    Use when your LC-MS peak table from MS-DIAL or similar software contains data from multiple ionization modes (positive and/or negative) and/or multiple chromatographic columns (e.
    0 installs
80. ▌
    Left Censored Missing Value Classification 2 · holobiomicslab

    Use when you have a metabolomics dataset (LC/MS or GC/MS) with missing values and need to determine which are below the limit of detection (LOD) or limit of quantification (LOQ). Left-censored classification is necessary when the missingness is informative—i.
    2 installs
81. ▌
    Mass Spectrometry Ionization Mode Handling 2 · holobiomicslab

    Use when when you have a feature table from LC-MS preprocessed data (e.g. from asari v1.9.2) and need to annotate ions and infer neutral mass.
    0 installs
82. ▌
    Mass Spectrometry Library Search Retrieval 2 · holobiomicslab

    Use when when you have an unknown MSMS spectrum (precursor m/z and fragment ions) and need to discover structurally related compounds from a spectral library.
    1 install
83. ▌
    Metabolite Annotation Network Architecture 2 · holobiomicslab

    Use when when annotating large-scale untargeted metabolomics datasets where reference library coverage is incomplete and you need to infer metabolite identities for unannotated compounds by propagating annotations from seed metabolites (database matches or prior curation) across both.
    2 installs
84. ▌
    Metabolite Candidate Ranking By Confidence 2 · holobiomicslab

    Use when you have a set of candidate metabolites for an unknown compound detected in a liquid chromatography–mass spectrometry (LC-MS) experiment, predicted RTs from a trained DNN model, and access to calibration molecules (minimum 10) that connect your observed chromatographic method to a source.
    0 installs
85. ▌
    Metabolite Set File Parsing And Validation 2 · holobiomicslab

    Use when when a user has prepared a custom collection of metabolite sets (e.g., from spectral fragmentation clustering, literature curation, or domain-specific grouping) in CSV or JSON format and wants to score their activity levels using PALS without modifying the core PALS codebase.
    0 installs
86. ▌
    Metabolomics Imputation Method Application 2 · holobiomicslab

    Use when your metabolomics dataset (LC/MS or GC/MS) contains missing values encoded as NA or zero that represent compounds below the instrument's limit of detection (LOD) or limit of quantification (LOQ), rather than values missing completely at random.
    0 installs
87. ▌
    Metabolomics Noise Perturbation Simulation 2 · holobiomicslab

    Use when when benchmarking or validating a pathway analysis method (such as PALS, ORA, or GSEA) on metabolomics data, you need quantitative evidence that the method's pathway rankings remain stable despite noise and missing peaks—conditions prevalent in real LC-MS/MS datasets.
    2 installs
88. ▌
    Positional Encoding For Spectral Sequences 2 · holobiomicslab

    Use when preparing mass spectrum input tensors for transformer encoder layers in IDSL_MINT.
    0 installs
89. ▌
    Pre Analytical Delay Effect Quantification 2 · holobiomicslab

    Use when you have uploaded a pre-analytical data table containing sample metadata, processing delay annotations (pre- and post-centrifugation timestamps or duration), and paired NMR metabolomic measurements for a sample cohort, and you need to quantify how delays at different time-points affect.
    0 installs
90. ▌
    Pytorch Transformer Backbone Instantiation 2 · holobiomicslab

    Use when when building a graph-based molecular property prediction model that must process both molecular structures (as heterogeneous graphs) and tabular metadata (chromatographic column parameters).
    2 installs
91. ▌
    Quality Control Sample Identification Lcms 2 · holobiomicslab

    Use when when you have XCMS-preprocessed LC-MS metabolomics data with a peak table and an accompanying covariate/metadata file that contains a 'SampleType' column, and you plan to apply QC-based quality filters (such as RSD filtering) or train classifiers for peak quality assessment.
    0 installs
92. ▌
    Reference Prediction Comparison Evaluation 2 · holobiomicslab

    Use when you have executed a structure annotation pipeline (like BAM) on a validation dataset for which ground-truth molecular structure annotations exist, and you need to assess whether the pipeline's predictions match the reference annotations at the required sensitivity and specificity.
    2 installs
93. ▌
    Spectral Feature Extraction And Annotation 2 · holobiomicslab

    Use when you have raw LC/MS data in mzML format and need to perform non-targeted screening to discover unknown chemical features without a predefined list of target compounds.
    0 installs
94. ▌
    Spectral Library Annotation Interpretation 2 · holobiomicslab

    Use when you have received chemical annotations from GNPS spectral library matching and need to (1) assess annotation confidence and validity for downstream analysis, (2) understand why the same chemical may appear under multiple GNPS annotation IDs, or (3) decide whether to collapse or deduplicate.
    0 installs
95. ▌
    Spectral Similarity Measure Implementation 2 · holobiomicslab

    Use when you have MSMS spectra from two or more compounds and need to identify which are structurally related. Use this skill when you want to rank spectrum pairs by similarity to discover novel analogs or validate structural assignments in untargeted metabolomics or natural products discovery.
    0 installs
96. ▌
    Spectrum Object Creation And Preprocessing 2 · holobiomicslab

    Use when when you have raw tandem mass spectrometry peak data (m/z and intensity pairs), precursor m/z, charge state, and adduct annotation for one or more compounds, and need to construct normalized spectrum objects suitable for downstream spectral alignment, modification site prediction, or.
    0 installs
97. ▌
    Stochastic Weight Averaging Implementation 2 · holobiomicslab

    Use when training a deeply regularized deep neural network on a large molecular feature dataset (e.
    2 installs
98. ▌
    Tabular Results Aggregation And Comparison 2 · holobiomicslab

    Use when when you have chemical annotations (GNPS matches) distributed across multiple sample groups (e.g., by sample type, extraction method, ionization source) with unequal numbers of files per group, and you need to compare enrichment fairly without group-size bias.
    2 installs
99. ▌
    Tanaka Physicochemical Descriptor Handling 2 · holobiomicslab

    Use when you have raw HPLC column metadata arrays containing Tanaka parameter blocks that will be fed into a featurizer for machine learning on retention times. Tanaka parameters are present but may contain string artifacts ('2.7 spp', '2.
    0 installs
100. ▌
     Cross Instrument Data Harmonization 2 · holobiomicslab

     Use when you have mass spectrometry spectral data from multiple instrument types (e.g., direct infusion MS, ambient ionization MS, laser desorption/ionization MS) and need to perform unified species discrimination or database scoring across all samples regardless of their source instrument.
     2 installs