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HolobiomicsLab

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1. ▌
   Isotope Corrected Image Quantitation 2 · holobiomicslab

   Use when after isotopic correction has been performed on MSI ion images and you need to convert normalized intensities into absolute quantitative values.
   0 installs
2. ▌
   Lipid Adduct Pairing By Neutral Mass 2 · holobiomicslab

   Use when when processing mass spectrometry imaging data with multiple adduct forms of the same lipid species, and you need to correct one adduct form (e.g. [M+H]+) for isotopic interference from a co-occurring adduct (e.g. [M+Na]+).
   0 installs
3. ▌
   Lipid Feature Annotation And Sorting 2 · holobiomicslab

   Use when after quantifying ion images in LipidQMap and before exporting to HDF5 format, when you need to organize per-feature metadata (lipid ID, class, adduct, m/z, internal standard flag) into aligned datasets that can be linked to intensity data via dimension scales and sorted for reproducible.
   0 installs
4. ▌
   Morphological Alignment Optimization 2 · holobiomicslab

   Use when you have two or more spatial omics datasets (e.
   0 installs
5. ▌
   Spatial Spot Coordinate Registration 2 · holobiomicslab

   Use when when you have paired spatial transcriptome and metabolome datasets with spot-based coordinates that need to be aligned for multi-modal integration.
   0 installs
6. ▌
   Mass Spectrometry Spectrum Tokenization 2 · 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
7. ▌
   Ms Dial Feature Detection And Alignment 2 · holobiomicslab

   Use when when you have raw LC-HRMS metabolomics data in .mzML or .abf format and need to perform untargeted feature detection with chromatographic alignment across multiple samples.
   0 installs
8. ▌
   Neutral Loss Calculation From Precursor 2 · 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
9. ▌
   Spectral Similarity Scoring Computation 2 · 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.
   2 installs
10. ▌
    Untargeted Metabolomics Data Processing 2 · holobiomicslab

    Use when you have two separate LC-MS untargeted metabolomic feature tables (e.
    2 installs
11. ▌
    Analyte Discrimination Machine Learning 2 · 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.
    1 install
12. ▌
    Chemical Annotation Matrix Construction 2 · holobiomicslab

    Use when you have selected a subset of public tandem MS files from ReDU/MassIVE that have been processed through GNPS spectral library matching, and you need to organize their chemical annotations into a matrix (rows = files, columns = annotated features) before performing PCA or other multivariate.
    0 installs
13. ▌
    Computational Environment Configuration 2 · holobiomicslab

    Use when at the start of any DaDIA pipeline execution, or whenever you are preparing to run a complex multi-package R workflow on a new system or after updating package managers.
    1 install
14. ▌
    Cross Dataset Generalization Assessment 2 · holobiomicslab

    Use when you have a pre-trained MS/MS spectral embedding model evaluated on one or more source datasets (GNPS, MoNA, MTBLS1572) and need to verify that it performs well on independent, high-quality curated spectral libraries to claim robustness.
    0 installs
15. ▌
    CSV Serialization For Mass Spectrometry 2 · holobiomicslab

    Use when you have generated or curated a lipid spectral library (with precursor m/z, adduct information, charge states, retention times, and fragmentation patterns) and need to export it for use in either Excalibur-based DDA experiments on an Orbitrap mass spectrometer, or in Skyline for targeted.
    0 installs
16. ▌
    Data Normalization In Mass Spectrometry 2 · 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
17. ▌
    Fda Repeatability Compliance Assessment 2 · holobiomicslab

    Use when you have completed NMR data quality control analysis and possess per-feature CV values, and you need to formally assess whether the metabolomic dataset meets FDA regulatory standards for downstream biomarker discovery or quantitative assays.
    0 installs
18. ▌
    Formula Assignment In Mass Spectrometry 2 · holobiomicslab

    Use when you have m/z values from mass spectrometry imaging (or similar MSI experiments) and need to assign molecular formulae to them. This is especially valuable when working with spatially-resolved metabolomics data where annotation precision lags behind traditional LC-MS approaches.
    0 installs
19. ▌
    Fragmentation Pattern Spectral Matching 2 · holobiomicslab

    Use when when you have detected m/z values from LC-IM-MS/MS that match a candidate CCS prediction database but require structural confirmation. Apply this skill to disambiguate isomers (e.
    1 install
20. ▌
    Injection Order Direction Specification 2 · holobiomicslab

    Use when when configuring a multi-well plate design (96-well, 384-well, or other format) in InjectionDesign for LC/GC-MS analysis and you need to specify whether analytical samples and QC controls should be injected row-by-row or column-by-column.
    1 install
21. ▌
    Knowledge Data Driven Layer Integration 2 · holobiomicslab

    Use when you have untargeted metabolomics data (MS/MS spectra) and need to annotate metabolites at scale.
    2 installs
22. ▌
    Lipid Derivatization Chemistry Modeling 2 · holobiomicslab

    Use when you have N-methyl-derivatized unsaturated sterol lipid structures (as SMILES or molecular formula) and need to predict their MS/MS fragmentation behavior before experimental acquisition, or to build a reference spectral library for isomer-level sterol identification in tissue samples.
    0 installs
23. ▌
    Lipid Fragmentation Pattern Application 2 · holobiomicslab

    Use when you have an enumerated list of lipid species (identified by class, fatty acid composition, and chain length) and need to generate theoretical precursor m/z values, fragment ion masses, and relative intensities for targeted or untargeted lipidomics experiments.
    0 installs
24. ▌
    Mass Spectrometry Feature Deconvolution 2 · holobiomicslab

    Use when you have a peak table from LC-MS peak picking software (e.
    0 installs
25. ▌
    Metabolite Prediction Pathway Selection 2 · holobiomicslab

    Use when when you have a small-molecule structure (SMILES, MOL, or SDF format) and need to predict its metabolic fate across one or more biological systems.
    2 installs
26. ▌
    Metabolomics Data Integration With Xcms 2 · holobiomicslab

    Use when you have untargeted LC-MS metabolomics data preprocessed with XCMS and need to filter out low-quality peak integrations that could introduce false positives or noise into metabolite quantification.
    0 installs
27. ▌
    Metabolomics Feature Quality Assessment 2 · holobiomicslab

    Use when after drift correction and before missing value imputation when your LC-MS peak table contains features with variable detection rates across samples.
    0 installs
28. ▌
    Molecular Graph Representation Encoding 2 · holobiomicslab

    Use when when you have a collection of molecular structures (as InChI strings, SMILES, or RDKit Mol objects) and need to feed them into a pretrained or transfer-learning neural network that expects both molecular graph topology and structural fingerprints as inputs.
    0 installs
29. ▌
    Ms Ms Spectrum Annotation Preprocessing 2 · holobiomicslab

    Use when you have raw LC-MS/MS data acquired in Data-Dependent Acquisition (DDA) mode and need to create a labeled training dataset for customized purification model development.
    0 installs
30. ▌
    Ms Spectra Extraction And Preprocessing 2 · 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
31. ▌
    Multi Dimensional Sample Stratification 2 · holobiomicslab

    Use when you have a parsed sample list with metadata (sample IDs, classification dimensions, QC designations) and need to generate a physical injection-plate layout that (1) will be run across multiple batches, (2) has a known confounding dimension (e.
    2 installs
32. ▌
    Network Based Metabolite Identification 2 · holobiomicslab

    Use when when you have m/z values from spatially-resolved mass spectrometry imaging (MSI) and need to predict their molecular formulae with high precision.
    1 install
33. ▌
    Network Graph Re Annotation Propagation 2 · holobiomicslab

    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 determine the structure of the modified compound.
    0 installs
34. ▌
    Neural Network Projection Module Design 2 · holobiomicslab

    Use when when you have 512-dimensional (or other fixed-size) representation vectors output from paired encoders processing augmented versions of the same input (e.
    0 installs
35. ▌
    Nontargeted Analysis Workflow Execution 2 · holobiomicslab

    Use when you have UPLC-HRMS data from ThermoFisher, Agilent, or other vendor instruments (converted via MSConvert if needed), organized as batch-processed files ready for MSThunder input, and you need to identify unknown organic pollutants with deep learning-assisted structure prediction and.
    0 installs
36. ▌
    Nps Structural Diversity Stratification 2 · holobiomicslab

    Use when you have a trained PS2MS deep learning model, a set of evaluation compounds (especially novel NPS analogues), and want to understand whether prediction confidence (softmax probabilities, uncertainties) degrades gracefully or sharply as structural distance from the training set increases.
    2 installs
37. ▌
    Numpress Compression Algorithm Encoding 2 · holobiomicslab

    Use when you have raw floating-point m/z and intensity arrays extracted from mass-spectrometry experiments (e.g., from mzML or mzXML files) and need to compress them for storage or transmission.
    0 installs
38. ▌
    Peak Boundary Definition And Validation 2 · holobiomicslab

    Use when after nontargeted peak detection has identified candidate peaks in LC-MS chromatograms, when you need to establish exact peak start/end retention times and extract peak-level metadata (intensity, width, shape) for downstream feature quality evaluation and annotation workflows.
    2 installs
39. ▌
    Qc Coefficient Of Variation Calculation 2 · holobiomicslab

    Use when after extracting NMR spectra and designating replicate QC samples (typically 10 samples run throughout the study), calculate CV for each metabolite feature to assess which signals are reproducible enough for downstream metabolite-phenotype association testing.
    0 installs
40. ▌
    Quantum Chemistry Structure Preparation 2 · holobiomicslab

    Use when when you have a collection of N-Me derived unsaturated sterol lipid identifiers or structures and need to generate predicted collision cross section (CCS) values for LC-IM-MS/MS analysis.
    0 installs
41. ▌
    Regression Model Evaluation Mae Metrics 2 · holobiomicslab

    Use when when you have trained a regression model on experimental retention times or similar continuous molecular property predictions and need to quantify its generalization performance on held-out test data.
    0 installs
42. ▌
    Retention Time Alignment Across Batches 2 · 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
43. ▌
    Signal Acquisition Error Quantification 2 · 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.
    2 installs
44. ▌
    Signal To Noise Ratio Calculation Peaks 2 · holobiomicslab

    Use when after elution peaks have been detected on composite mass tracks using local maxima and prominence detection, before reporting features in the final feature table.
    2 installs
45. ▌
    Spatial Metabolomics Feature Annotation 2 · holobiomicslab

    Use when your spatial metabolomics dataset contains raw m/z features (e.g., from MALDI-MS imaging or LC-MS/MS) without metabolite annotations, and you have selected a reference database and adduct type appropriate for your ionization mode and biological sample.
    0 installs
46. ▌
    Spectral Data Input Handling Mgf Format 2 · holobiomicslab

    Use when when you have raw MS/MS mass spectrometry data and need to submit it to the Mass2SMILES Docker inference container for structure and functional group prediction.
    0 installs
47. ▌
    Spectral Overlay Rendering Multi Sample 2 · holobiomicslab

    Use when when you have aligned peak-alignment data from a preceding molecular networking task (structured as a table with peak intensity, m/z, retention time, and alignment quality metrics) and need to visualize and interactively filter peaks across multiple spectra to support comparative mass.
    0 installs
48. ▌
    Tensorflow Cpu Runtime Parameter Tuning 2 · holobiomicslab

    Use when deploying Mass2SMILES on a TensorFlow-CPU build and you need to optimize inference throughput on multi-core systems. This is particularly necessary when GPU inference is unavailable due to CUDA driver incompatibility, or when inference hardware has variable core counts (e.
    2 installs
49. ▌
    Tof Ms Signal Enhancement Low Abundance 2 · holobiomicslab

    Use when your raw TOF-MS data (Agilent MassHunter .d format) exhibits jagged, artifact-prone peaks in low-abundance ions that compromise peak quality assessment or when you need to improve signal-to-noise before ion mobility demultiplexing or peak deconvolution.
    0 installs
50. ▌
    Training Data Loading And Preprocessing 2 · holobiomicslab

    Use when you have downloaded raw LC-MS spectral peak data from a public repository (e.g., DOI 10.25345/C5FD2F) and need to ingest it into memory and prepare it in the format expected by a TensorFlow/Keras neural network classifier.
    1 install
51. ▌
    Transformer Architecture Implementation 2 · holobiomicslab

    Use when when building a neural network to map between mass spectrometry spectra and molecular properties (e.g., fingerprints, SMILES, or fragment ions) where sequential or spectral feature dependencies must be captured.
    0 installs
52. ▌
    Untargeted Metabolomics Data Processing 3 · holobiomicslab

    Use when you have untargeted MS2 spectral data (from LC-MS/MS or similar instruments) and need to assign metabolic pathway context to detected compounds when standard spectral library matching is unavailable or insufficient.
    0 installs
53. ▌
    Graph Neural Network Implementation 2 · holobiomicslab

    Use when when your input includes molecular structures (SMILES, conformers) and you need to predict a continuous property (e.g., CCS, binding affinity, solubility) that depends on molecular connectivity and spatial relationships.
    0 installs
54. ▌
    Jupyter Notebook Development Python 2 · holobiomicslab

    Use when when building reproducible Python-based computational workflows that must serve both beginner and expert users; when the analysis requires interactive parameter tuning, file upload capability, or real-time result visualization;
    1 install
55. ▌
    Jupyter Notebook Workflow Execution 2 · holobiomicslab

    Use when you have a curated training dataset of molecular structures with known CCS values, a target set of ≤10,000 molecules requiring CCS predictions, and need to apply a pre-configured Sklearn-based machine learning model within a reproducible, browser-accessible environment.
    0 installs
56. ▌
    Metabolite False Positive Filtering 2 · holobiomicslab

    Use when you have ion-mobility mass spectrometry metabolomics data with putative metabolite identifications (e.g., from database matching) and want to reduce false positives by cross-validating compound identities against machine-learned CCS predictions.
    0 installs
57. ▌
    Chemical Space Similarity Computation 2 · holobiomicslab

    Use when you have retrieved multiple candidate structures from a molecular structure database (e.g., PubChem, HMDB) for an unknown compound, and you have predictions of structurally related metabolites from a deep-learning mass spectral model (e.g., DeepMASS2).
    0 installs
58. ▌
    Classification Performance Evaluation 2 · holobiomicslab

    Use when after running inference on test mass spectrometry spectra with a trained deep learning model (e.g., PS2MS) to verify that class label predictions and confidence scores match expected reference outputs.
    0 installs
59. ▌
    Interactive Filter Control Design Web 2 · holobiomicslab

    Use when when you have a web-based visualization of aligned mass spectrometry peaks (m/z, intensity, retention time, alignment quality metrics) and need users to interactively explore subsets of those peaks by applying constraints on intensity thresholds, alignment score cutoffs, or peak.
    0 installs
60. ▌
    Neural Network Encoder Implementation 2 · holobiomicslab

    Use when when you need to benchmark multiple encoder types (e.g., FFN vs. GNN) on the same predictive task and require evidence that performance differences reflect genuine architectural trade-offs rather than suboptimal tuning.
    0 installs
61. ▌
    Neutral Mass Inference Via Regression 2 · holobiomicslab

    Use when use this skill after khipu has assigned observed ions to grid positions (isotope and adduct combinations). Apply it when you have a connected subnetwork of feature ions that have been matched to known isotope and adduct patterns and need to estimate the neutral mass of the parent compound.
    0 installs
62. ▌
    Nonparametric Reproducibility Ranking 2 · holobiomicslab

    Use when you have high-dimensional replicate experiment data (e.
    0 installs
63. ▌
    Peak Background Binary Classification 2 · holobiomicslab

    Use when you have LC-HRMS profile-mode chromatograms with extracted local maxima exported as standardized 2D rt×mz areas, and you need to disambiguate true chromatographic peaks from background signals (including wall artifacts and noise) at scale.
    0 installs
64. ▌
    Spectral Fragment Identifier Matching 2 · holobiomicslab

    Use when when you have downloaded fragment records from separate experimental and predicted online databases and need to verify that each fragment can be traced back to a valid compound entry in a reference compound database (e.g., SDF-format DNA adduct compound collection).
    2 installs
65. ▌
    Domain Specific Masst API Integration 2 · holobiomicslab

    Use when your research involves searching MS/MS spectra against multiple curated taxonomic or domain-specific databases (microbial, plant, tissue, microbiome, or food origin) and you need to aggregate, compare, and visualize matching results across all domains in a single interface.
    0 installs
66. ▌
    Latent Space Dimensionality Reduction 2 · holobiomicslab

    Use when you have imaging mass spectrometry (IMS) datasets where peak intensities are high-dimensional and sparse, and you need to extract compressed latent features that preserve spatial adjacency relationships and enable iterative automatic peak picking to identify marker ions.
    0 installs
67. ▌
    Mass Spectrometry Image Preprocessing 3 · holobiomicslab

    Use when you have raw or preprocessed single-channel (2D array) or multi-channel (spectral) ion images from mass spectrometry imaging (MSI) data and need to train a contrastive deep learning model.
    0 installs
68. ▌
    Msi Data Processing Speed Measurement 2 · holobiomicslab

    Use when when you need to validate that MSI software (e.g., LipidQMap) achieves documented processing speeds on your target hardware, or when you need to establish a performance baseline before deploying the software for high-throughput imaging studies.
    2 installs
69. ▌
    Natural Isotope Abundance Calculation 2 · holobiomicslab

    Use when when processing mass spectrometry imaging (MSI) data in positive ion mode where both [M+H]+ and [M+Na]+ adducts are present for the same lipid species, and you observe intensity overlap in [M+H]+ ion images caused by the isotopic fine structure of [M+Na]+ adducts.
    0 installs
70. ▌
    Parameter Sharing In Siamese Networks 2 · holobiomicslab

    Use when when processing paired augmented versions of the same input (e.g., two augmented ion images in COL or ISO mode) and you need to learn meaningful low-dimensional representations via contrastive loss.
    0 installs
71. ▌
    Activity Score Computation And Reporting 2 · holobiomicslab

    Use when you have preprocessed metabolite intensity data (log2-transformed, zero-mean unit-variance standardized) mapped to compound annotations, and you need to derive activity scores for a set of metabolite groups (pathways, Molecular Families, Mass2Motifs, or custom metabolite sets) to rank them.
    0 installs
72. ▌
    Chemical Database Querying And Retrieval 2 · holobiomicslab

    Use when you have BioTransformer-predicted metabolite structures (in SMILES or InChI format) and need to identify which known compounds in public databases match those structures.
    0 installs
73. ▌
    Chromatographic Method Transfer Learning 2 · holobiomicslab

    Use when you have experimental RT measurements from a source chromatographic method and need to predict RTs for the same molecules on a target chromatographic method, but lack a large calibration dataset (typical scenario: 10–100 molecules with ground truth RTs on both methods).
    2 installs
74. ▌
    Comparative Enrichment Method Evaluation 2 · holobiomicslab

    Use when you are selecting a pathway enrichment method for metabolomics peak data and need to assess which method will remain stable when your data contains noise, dropout, or missing identifications.
    1 install
75. ▌
    Contrastive Learning Loss Implementation 2 · holobiomicslab

    Use when when you have paired augmented ion images processed through ResNet18 encoders producing 512-dimensional representation vectors, and you need to learn meaningful low-dimensional representations without labeled data by enforcing that augmentations of the same image remain similar while.
    2 installs
76. ▌
    Cross Method Chromatographic Scalability 2 · holobiomicslab

    Use when you have a pretrained RT-Transformer model checkpoint from a large, well-characterized chromatographic dataset (e.g., SMRT) and need to predict retention times for a different chromatographic method or instrument condition represented in a smaller, domain-specific dataset (e.g., PredRet).
    0 installs
77. ▌
    Deep Neural Network Latent Space Mapping 2 · holobiomicslab

    Use when you have a pre-trained DNN model for retention time prediction and need to adapt it to a new chromatographic method or instrument where you have only 10–20 calibration molecules with known retention times;
    0 installs
78. ▌
    Documentation And Metadata Modernization 2 · holobiomicslab

    Use when a mature scientific package (e.g., Mummichog 3) is being migrated to a new GitHub organization that enforces standardized project structure, and the current setup.py, pyproject.toml, requirements.txt, .
    0 installs
79. ▌
    Error Metric Comparison And Benchmarking 2 · holobiomicslab

    Use when you have predicted retention times from one or more machine learning models (DNN, Gaussian Process, or ensemble) applied to small-molecule chromatography data, along with corresponding experimental ground-truth retention times, and need to quantify prediction accuracy and rank competing.
    1 install
80. ▌
    Feature Matrix Normalization And Scaling 2 · holobiomicslab

    Use when you have a heterogeneous feature matrix combining molecular descriptors (from RDKit/mordred) and chromatographic metadata (column length, temperature, pH, flow rate, particle size) with different physical units, ranges, and scales.
    0 installs
81. ▌
    Fragmentation Pattern Similarity Scoring 2 · 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).
    2 installs
82. ▌
    Gnps Spectral Library Compound Retrieval 2 · holobiomicslab

    Use when you have GNPS library accession IDs (e.g. CCMSLIB00011906190) for a reference compound and a chemically or biologically modified analog, and need to load their full MS/MS spectra and structural annotations to set up a modification-finding analysis.
    0 installs
83. ▌
    Identifier Format Parsing And Validation 2 · holobiomicslab

    Use when you receive mass spectrometry data through heterogeneous identifier formats—specifically when the input could be a GNPS Task ID, a Universal Spectrum Identifier (USI), or a Feature-Based Molecular Networking (FBMN) identifier—and you need to programmatically determine which format was.
    0 installs
84. ▌
    Inference Model Cpu Thread Configuration 2 · holobiomicslab

    Use when when running Mass2SMILES inference on a TensorFlow-CPU build (e.g., delser292/mass2smiles:final container) and you need to optimize inference speed by controlling CPU core allocation.
    0 installs
85. ▌
    Mass Spectrometry Data Format Conversion 2 · 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
86. ▌
    Mass Spectrometry File Format Conversion 2 · 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.
    2 installs
87. ▌
    Metabolite Detection Matrix Construction 2 · holobiomicslab

    Use when after GNPS spectral library matching has been completed on a batch of MS2 spectra from public MassIVE datasets and you need to aggregate chemical annotations into a tabular format suitable for downstream comparative metabolomics, co-analysis, or chemical explorer visualizations across.
    0 installs
88. ▌
    Metabolite Edge Scoring Dbedges Bioedges 2 · holobiomicslab

    Use when you have a measured m/z value from spatially-resolved metabolomics or mass spectrometry imaging and need to assign a molecular formula with high confidence. Use it specifically when you have access to a pre-constructed formula network (KnownSet database) linking 2.
    0 installs
89. ▌
    Molecular Structure Graph Representation 2 · holobiomicslab

    Use when when you have a set of chemical structures (SMILES strings or SDF files) that need to be processed for training a graph neural network model on molecular property prediction tasks, specifically when the target property (e.
    0 installs
90. ▌
    Ms Ms Fragment Assignment And Annotation 2 · holobiomicslab

    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 lipid, calculate exact m/z values, estimate relative intensities, and produce a machine-readable reference table for.
    0 installs
91. ▌
    Multiple Testing Correction Metabolomics 2 · holobiomicslab

    Use when you have computed raw p-values from partial Spearman correlations (or other univariate tests) between each metabolite in a SummarizedExperiment object and a phenotype of interest, adjusted for epidemiological confounders (e.
    1 install
92. ▌
    Neutral Mass Inference From Ion Ensemble 2 · holobiomicslab

    Use when you have a connected subnetwork of feature ions that have been validated as belonging to the same empirical compound (khipu instance), with isotope and adduct edges assigned, and you need to estimate the true neutral mass M0 rather than relying on any single observed m/z.
    0 installs
93. ▌
    Nontargeted Metabolomics Data Processing 2 · holobiomicslab

    Use when you have raw LC-MS data in vendor or mzML format and need to systematically discover and extract all detectable metabolite features across the full retention time range, without predefined target lists.
    0 installs
94. ▌
    Pathway Activity Decomposition Via Plage 2 · holobiomicslab

    Use when you have a log2-transformed, standardized peak intensity matrix (rows = metabolite features, columns = samples) with compound annotations mapped to curated pathway databases (KEGG, Reactome, or custom metabolite sets), and you need to rank pathways by their activity level while tolerating.
    0 installs
95. ▌
    Peak Prominence Calculation Local Maxima 2 · holobiomicslab

    Use when when processing LC-MS mass tracks (EICs) and you need to identify genuine chromatographic peaks rather than noise artifacts.
    0 installs
96. ▌
    Python Package Migration And Refactoring 2 · holobiomicslab

    Use when you have a mature Python package (e.g., Mummichog 2.x) that needs to be relocated to a new GitHub organization (e.
    0 installs
97. ▌
    Retention Time Prediction Chromatography 2 · holobiomicslab

    Use when you have a new chromatographic dataset with molecular structures (as InChI or SMILES) and experimentally measured retention times, and you want to predict retention times for unannotated metabolites or validate predictions on a held-out test set without retraining from scratch.
    2 installs
98. ▌
    Robust Statistical Spread Quantification 2 · holobiomicslab

    Use when after drift correction of LC-MS peak intensity data, when you need to identify metabolic features with excessive internal spread (within-group variability in QC samples) or poor biological-to-technical reproducibility (QC-versus-sample spread).
    0 installs
99. ▌
    Spectral Clustering And Feature Grouping 2 · holobiomicslab

    Use when you have raw MS/MS feature data with m/z, retention time, and fragmentation spectra from an untargeted metabolomics experiment, and you need to annotate reaction-derived metabolites of xenobiotics without relying on a priori targeted methods.
    1 install
100. ▌
     Spectral Library Query Reference Pairing 2 · holobiomicslab

     Use when when evaluating a trained spectral embedding model on publicly available datasets (GNPS, MoNA, MTBLS1572, MassBank, or MassSpecGym) and you need to report averaged performance metrics with standard deviation to demonstrate robustness and reproducibility.
     0 installs