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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Extracted Ion Chromatogram Peak Shape Similarity · holobiomicslab

   Use when after features have been grouped by retention time similarity and abundance correlation across samples, but before downstream annotation or compound identification.
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2. ▌
   Ft Icr Ms Data Preprocessing And Quality Control · holobiomicslab

   Use when when you have raw or processed FT-ICR MS peak-abundance .
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3. ▌
   High Resolution Mass Spectrometry Interpretation · holobiomicslab

   Use when you have centroided LC- or GC-HRMS data (in mzML format, ideally from data-dependent acquisition) and need to identify potential PFAS candidates from a large feature list.
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4. ▌
   Isotopic Envelope Generation At Fixed Enrichment · holobiomicslab

   Use when when you have a peptide sequence, MS2 fragment charge states, and a known isotope enrichment fraction (e.g., 1.
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5. ▌
   Machine Learning Model Application To Lipidomics · holobiomicslab

   Use when you have MS-DIAL lipid identifications from an Orbitrap or TOF mass spectrometer and need to remove spurious or low-confidence assignments before downstream metabolomics analysis.
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6. ▌
   Mass Binning And Tokenization For Topic Modeling · holobiomicslab

   Use when you have extracted and intensity-normalized fragment ion masses and neutral loss values from MS/MS spectra and need to prepare them for unsupervised topic modeling to discover recurring fragmentation motifs.
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7. ▌
   Mass Spectrometry Data Visualization With Pandas · holobiomicslab

   Use when your input is a Pandas DataFrame containing mass spectrometry measurements (m/z and intensity columns for spectra, retention time and intensity for chromatograms, or x, y, z for 2D/3D peak maps) and you need to generate static plots (matplotlib) or interactive web-based visualizations.
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8. ▌
   Mass Spectrometry Dataset Handling Preprocessing · holobiomicslab

   Use when you have raw or semi-processed MS/MS spectra in MSP format (e.g., from GNPS, Orbitrap instruments) and need to feed them into MSBERT or similar transformer-based embedding models for library matching, clustering, or similarity scoring.
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9. ▌
   Mass Spectrometry Instrument Resolution Modeling · holobiomicslab

   Use when when correcting LC-MS fractional abundances of measured isotopologues (FAM) from isotope labeling experiments where instrument resolution (e.
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10. ▌
    Mass Spectrometry Reference Database Integration · holobiomicslab

    Use when you have individual MS/MS spectra or batch .mgf files from untargeted metabolomics experiments and need to search them against domain-specific reference libraries (e.
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11. ▌
    Metabolite Feature Extraction And Quantification · holobiomicslab

    Use when after retention-time correction and data alignment have been completed on centroided LC-MS data (mzML or mzXML format).
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12. ▌
    Multidimensional Feature Extraction From Spectra · holobiomicslab

    Use when you have preprocessed MS/MS spectral data (normalized peak intensities and m/z values) and need to transform spectra into fixed-dimensional molecular embeddings for candidate matching against a reference database, especially when direct spectral comparison or classical fingerprinting.
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13. ▌
    Neural Network Based Molecular Formula Inference · holobiomicslab

    Use when you have MS/MS spectra with unknown precursor m/z values and need to assign the most likely chemical formula and adduct type (e.g., [M+H]+, [M+Na]+, [M+K]+) in a de novo setting where spectrum database matching is unavailable or undesirable.
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14. ▌
    Peak Intensity Chromatographic Property Analysis · holobiomicslab

    Use when you have a filtered MS-DIAL peak list (post-generic filtering) containing m/z, retention time, and peak intensity metrics, and you need to group LC-MS features into clusters to reduce redundancy before parental signal extraction.
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15. ▌
    Peptide Modification Representation And Handling · holobiomicslab

    Use when when you have an observed MS/MS spectrum and need to annotate fragment peaks against a known modified peptide sequence. Specifically: (1) you possess a peptide amino acid sequence with known or predicted post-translational modifications at specific positions;
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16. ▌
    Python Module Integration And Pipeline Extension · holobiomicslab

    Use when you have developed new scoring logic (e.g., average inchikey score, neighbourhood score) for an MS/MS spectral analogue search tool and need to embed these components into an existing production pipeline that uses a random forest to combine multiple features for candidate re-ranking.
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17. ▌
    Quantum Chemistry Based Fragmentation Prediction · holobiomicslab

    Use when when you have SMILES strings or molecular formulae for N-Me derivatized unsaturated sterol lipids and need to generate theoretical MS/MS spectra (predicted fragment m/z values and intensities) to compare against experimental LC-IM-MS/MS data before performing CCS prediction or downstream.
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18. ▌
    R Bioconductor Summarizedexperiment Manipulation · holobiomicslab

    Use when when converting raw metabolomics data (tab-delimited text files, Sciex OS exports) into a structured object for batch processing, or when you need to organize compound-level measurements (assays), sample metadata (colData), and feature annotations (rowData) in a single container that.
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19. ▌
    Retention Time Calibration Via Lowess Regression · holobiomicslab

    Use when after mass track extraction and alignment across samples, when preparing to detect elution peaks on composite mass tracks. Use this when inter-sample retention time variation exceeds acceptable alignment tolerance (e.
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20. ▌
    Spectral Tensor Representation And Preprocessing · holobiomicslab

    Use when when preparing MS/MS spectra from .msp files for transformer-based deep learning models in IDSL_MINT. Specifically: you have raw spectral data with variable peak counts and need fixed-size tensor inputs;
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21. ▌
    Systematic Mass Calibration And Drift Correction · holobiomicslab

    Use when when processing multiple LC-MS samples in a cohort study and MassGrid construction reveals that anchor mass tracks (13C/12C isotope or Na/H adduct pairs) in non-reference samples deviate systematically from the reference sample's m/z values by >1 ppm.
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22. ▌
    Targeted Peak Detection Screening And Validation · holobiomicslab

    Use when you have centroided mzML LC–MS data, a curated list of target compounds (with theoretical m/z, expected retention time, and polarity), and you need to confirm target presence and extract quantitative metrics (area under curve, max intensity, signal-to-noise ratio, peak correlation, point.
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23. ▌
    Transition List Formatting For Targeted Analysis · holobiomicslab

    Use when you have generated or assembled a lipid spectral library with precursor m/z values, adduct information, and fragmentation patterns, and you need to import those spectra into Skyline for targeted data-independent or parallel-reaction-monitoring (PRM) analysis.
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24. ▌
    Molecular Structure Prediction Out Of Distribution · holobiomicslab

    Use when your goal is to assess whether a pretrained NMR2Struct model trained on molecules ≤19 heavy atoms can generalize to larger, more complex molecules, or whether accuracy degrades significantly.
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25. ▌
    Environment Validation And Verification · holobiomicslab

    Use when after installing ENPKG or any component of the workflow via conda/pip dependency manifests and before executing workflow scripts.
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26. ▌
    File Path Abstraction And Normalization · holobiomicslab

    Use when a Shiny application or R package is confirmed to work on one OS (e.g., Windows only) but fails to initialize or run on others due to unresolved file path conventions, system library calls, or OS-specific package dependencies.
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27. ▌
    Hypergeometric Distribution Calculation · holobiomicslab

    Use when when you have raw strain correlation scores (or similar overlap-based metrics) computed across genomic cluster family (GCF) and molecular family (MF) pairs of varying sizes, and you need to make those scores comparable across links with different GCF sizes (#G), MF sizes (#m), and.
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28. ▌
    Installation Validation And Diagnostics · holobiomicslab

    Use when after installing a package via conda or pip from a distribution channel (e.g., Bioconda, PyPI), run this skill to confirm the installation succeeded and that critical submodules are importable before proceeding to use the package in analysis workflows.
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29. ▌
    Metabolic Gap Filling Community Context · holobiomicslab

    Use when you have consensus metabolic reconstructions for all members of a microbial or plant community (e.
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30. ▌
    Molecular Ccs Prediction Model Training · holobiomicslab

    Use when you have a curated dataset of small molecules with SMILES, optional 3D coordinates, adduct information, and experimentally measured CCS values (in Ångströms or similar units), and you want to train a GNN model to predict CCS on held-out test molecules.
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31. ▌
    Ms Signal Correction Strategy Selection · holobiomicslab

    Use when you have loaded raw MS intensity tables into QuantyFey and observe or suspect intensity drift artifacts across your measurement sequence. Drift is especially likely in long-running targeted MS experiments where calibration curves or internal standards show systematic variation over time.
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32. ▌
    Natural Product Chemical Representation · holobiomicslab

    Use when you have a set of natural product molecules (or suspected natural products) in SMILES, InChI, or SDF format and need a chemical representation suitable for biosynthetic classification, structural screening, or machine learning tasks where standard generic fingerprints (e.
    0 installs
33. ▌
    Neural Network Projection Module Design · 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.
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34. ▌
    Nps Structural Diversity Stratification · 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.
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35. ▌
    Pathway Database Filtering By Detection · holobiomicslab

    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 for pathway enrichment. The skill is essential if your detection method has known sensitivity limits (e.
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36. ▌
    Plotly 3d Surface Scatter Visualization · holobiomicslab

    Use when you have mass spectrometry data (m/z, retention time, intensity) loaded into a Pandas DataFrame and need to explore the full 3D structure of a peak map interactively, particularly when static 2D heatmaps obscure important intensity relationships or when stakeholders require browser-based.
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37. ▌
    Pooled Statistical Significance Testing · holobiomicslab

    Use when when you have validated link annotations from multiple independent datasets (≥2), individual scoring functions with per-dataset enrichment p-values, and you want to test whether a combined scoring strategy (e.
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38. ▌
    Python Class Design With Dunder Methods · holobiomicslab

    Use when when you need to enable bracket notation (e.g., handler[5]) for random access to blocks within a large compressed or remote data source, or when you want to support both random access and sequential iteration over data without materializing all records upfront.
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39. ▌
    Python Package Installation From Source · holobiomicslab

    Use when when you need to verify a Python package installs successfully from a cloned or local repository, validate that all tests pass after installation, or prepare a development environment for contributing to the package.
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40. ▌
    Regression Model Evaluation Mae Metrics · 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.
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41. ▌
    State Dict Serialization And Extraction · holobiomicslab

    Use when after training a multi-component neural network architecture (e.
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42. ▌
    Statistical Score Distribution Analysis · holobiomicslab

    Use when when you have run the same mass spectrum through molecular formula assignment under different parameter settings (e.
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43. ▌
    Structured Data Compilation From Readme · holobiomicslab

    Use when when a scientific software repository documents multiple standalone tools, web applications, or resources with associated metadata (URLs, publications, taxonomic coverage) in its README, and you need to create a machine-readable inventory for downstream indexing, validation, or reuse.
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44. ▌
    Two Layer Architecture Dispatch Testing · holobiomicslab

    Use when when you need to verify that a wrapper package (e.g., rawrr) correctly bridges R and a managed .NET assembly (such as RawFileReader), specifically to confirm that internal dispatch functions can retrieve assembly location and version string before attempting actual spectral data extraction.
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45. ▌
    Abstract Method Subclassing Filter Base · holobiomicslab

    Use when when you need to apply domain-specific filtering logic to compounds during Pickaxe expansion—for example, retaining only compounds within a Tanimoto similarity threshold to known targets, or compounds matching experimentally detected masses.
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46. ▌
    Batch Effect Correction In Metabolomics · holobiomicslab

    Use when you have a preprocessed and normalized lipid abundance matrix with documented batch identifiers and experimental group assignments, and you need to perform differential abundance testing across simple or complex experimental designs (multi-factor, repeated measures) where batch effects.
    0 installs
47. ▌
    Batch Effect Correction Reference Based · holobiomicslab

    Use when when you have log-transformed metabolite abundance data from multiple batches (e.
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48. ▌
    Candidate Set Generation For Annotation · holobiomicslab

    Use when when you have raw or unprocessed PubChem compound records and need to produce a curated set of candidate metabolite structures for input to MAGMa job calculations.
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49. ▌
    Cardinal Object Structure Understanding · 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.
    0 installs
50. ▌
    Cell Type Protein Profiling Integration · 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.
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51. ▌
    Chemical Structure Format Normalization · holobiomicslab

    Use when when integrating chemical structure data from multiple source databases that represent the same compound in different notations (e.
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52. ▌
    Collision Cross Section Bias Estimation · holobiomicslab

    Use when when you have IM-MS lipidomics data spiked with U13C labeled lipid internal standards (e.g., fully labeled yeast extract) and want to assess whether measured CCS values deviate systematically from expected values in the DTCCS_N2 reference library.
    0 installs
53. ▌
    Community Metabolic Pathway Integration · holobiomicslab

    Use when you have multiple draft metabolic models (in JSON, XML, or SBML format) representing individual members or assembly variants of a community—such as Arabidopsis thaliana-associated microbiota—and need a single integrated model that captures the consensus metabolic potential while resolving.
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54. ▌
    Conformer Filtering Threshold Selection · holobiomicslab

    Use when after RDKit has generated a large ensemble of 3D conformers for a molecule (typically hundreds to thousands), you need to reduce computational burden before quantum-chemical single-point energy evaluation.
    0 installs
55. ▌
    Cross File Version Consistency Checking · holobiomicslab

    Use when before initiating a release branch workflow for a multi-module Maven project, particularly when the repository contains multiple pom.xml files at different directory levels and a release branch naming convention (e.g., 'release/X.Y.Z') is planned.
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56. ▌
    Cross Validation Performance Evaluation · holobiomicslab

    Use when when you have paired microbiome and metabolome count data and need to estimate how well a neural network or regression model can predict metabolite abundances from microbial features without overfitting to a single held-out test set.
    0 installs
57. ▌
    CSV Delimiter Parsing And Configuration · holobiomicslab

    Use when when uploading a new mass spectrometry data file to Punc'data in CSV or delimited-text format, before attempting to map columns to their semantic roles (m/z value, intensity, formula).
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58. ▌
    Dataset Serialization For Deep Learning · holobiomicslab

    Use when after generating aligned multimodal feature tensors from molecular structures (graph-based features, Morgan fingerprints, and physicochemical descriptors) and before initiating model training loops.
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59. ▌
    Deep Learning Model Architecture Design · holobiomicslab

    Use when you have extracted molecular features (voxel projected areas, molecular graphs, m/z values, adduct encodings) and need to build a predictive model to map these features to a continuous molecular property (CCS).
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60. ▌
    Dictionary Lookup And Cross Referencing · holobiomicslab

    Use when after integrating and curating raw structure-organism pairs from multiple heterogeneous databases, use this skill when you need to verify that each pair and its associated metadata (literature citations, organism taxonomy, chemical identifiers) exist in your authoritative reference.
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61. ▌
    Distance Matrix Computation For Samples · holobiomicslab

    Use when after batch effect removal and data integration, when you have a feature-by-sample matrix (finalData) and wish to separate and visualize sample groups by their metabolomic profiles using clustering methods such as hierarchical clustering analysis (HCA).
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62. ▌
    Docker Containerized Pipeline Execution · holobiomicslab

    Use when you have raw mass spectrometry data converted to MS1 format and need to predict peptide features (charge, isotope count, retention time) without installing complex dependencies or configuring GPU/Python environments locally.
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63. ▌
    Dynamic Branch Cutting Module Detection · holobiomicslab

    Use when after constructing a hierarchical dendrogram from a biweight midcorrelation dissimilarity matrix of metabolite measurements, when your dendrogram exhibits complicated structure (multiple scales, varying branch heights) that would be poorly captured by a single fixed-height cutoff, and you.
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64. ▌
    Elemental Ratio Histogram Visualization · holobiomicslab

    Use when after loading a numeric elemental ratio column (H/C, O/C, N/C, etc.) from a CSV file into Punc'data, when you need to visualize the distribution of molecular formulas across a sample and want bin spacing to adapt automatically: narrow bins (0.1) for low-range data (span ≤ 3.
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65. ▌
    Enrichment Visualization And Annotation · holobiomicslab

    Use when after pathway enrichment analysis has been executed by clusterProfiler or biotranslator on differentially expressed features filtered by layer-specific p-value cutoffs (genes_genespval=1, mirna_genespval=1, proteins_genespval=0.5, lipids_genespval=0.5).
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66. ▌
    Fold Change Significance Interpretation · holobiomicslab

    Use when when you have differential expression results with both fold-change and p-value columns from a CSV file (e.g., volcano_example.
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67. ▌
    Gpu Accelerated Neural Network Training · holobiomicslab

    Use when when you have a trainable neural network model (e.g., MSNovelist), labeled training data with known input/output pairs, GPU resource availability on a compute cluster, and need to optimize model weights via backpropagation.
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68. ▌
    Gpu Capability Detection And Validation · holobiomicslab

    Use when after setting up a conda/pip environment with PyTorch and CUDA, before loading pretrained model weights or running inference/training pipelines.
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69. ▌
    HTTP Endpoint Connectivity Verification · holobiomicslab

    Use when after deploying a web service in a Docker container with port mapping (e.g., -p 8888:8080), verify that the application is running and responding to HTTP requests at the mapped endpoint.
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70. ▌
    Instrumental Noise Spike Identification · holobiomicslab

    Use when you have raw LA-ICP-MS image data (line-by-line, spot-wise, or ablation-time-aligned) that exhibits isolated high-intensity or low-intensity pixels inconsistent with neighboring pixels.
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71. ▌
    Internal Standard Intensity Calibration · holobiomicslab

    Use when you have added a known internal standard compound to your nano-DESI MSI sample and want to correct for pixel-to-pixel variation in ionization efficiency or sample deposition.
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72. ▌
    Isotope Mass Table Reference Management · holobiomicslab

    Use when when building a mass spectrometry analysis pipeline that requires exact mass lookups, molecular formula validation, or isotope abundance predictions. Specifically: (1) you are constructing a MolecularFormula class that needs to validate element symbols against known isotopes;
    0 installs
73. ▌
    Lexical Tokenization And Grammar Design · holobiomicslab

    Use when you need to enable users to express complex domain-specific queries in a natural, succinct syntax—particularly when SQL patterns are familiar but must be augmented with domain assumptions (e.
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74. ▌
    Log Transformation And Scale Adjustment · holobiomicslab

    Use when raw metabolomics peak intensity data exhibits right-skewed distributions with heteroscedastic variance across metabolites and samples, or when combining multiple normalization methods (e.
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75. ▌
    M Z Annotation Reduction Quantification · 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.
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76. ▌
    Machine Learning Model Training Sklearn · holobiomicslab

    Use when your metabolomics analysis pipeline requires CCS value prediction for ion-mobility mass spectrometry data, you have access to a curated training set of known metabolites with experimentally validated CCS values, and you plan to predict CCS values on target datasets containing 10,000+.
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77. ▌
    Mass Grid Index Traversal And Retrieval · holobiomicslab

    Use when when you have constructed a MassGrid (m/z-aligned mass tracks across multiple samples) and need to retrieve all sample-specific mass tracks for a given m/z value in order to sum their intensities, apply retention time calibration, or construct composite mass track objects for peak.
    0 installs
78. ▌
    Mass Recalibration Lock Mass Correction · holobiomicslab

    Use when converting mzML files to imzML format for imaging mass spectrometry data and you have a known internal standard (lock mass) whose exact m/z value is available. Use it specifically during the metadata annotation stage (iw_utils.
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79. ▌
    Mass Spectrometry Drift Time Processing · holobiomicslab

    Use when when you have raw ion mobility-mass spectrometry data (drift times, m/z values, and frame metadata) from DTIMS-MS, TWIMS-MS, or SLIM-based instruments and need to compute CCS values for structural characterization or database matching.
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80. ▌
    Matrix Subsetting With Index Reordering · holobiomicslab

    Use when when you need to subset a backend containing multiple MS spectra to a user-defined subset (e.
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81. ▌
    Metabolite Benchmark Dataset Validation · holobiomicslab

    Use when after mzRAPP has exported a benchmark CSV file from processing a batch of centroided mzML files (e.
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82. ▌
    Metabolite Feature Grouping By Compound · holobiomicslab

    Use when after XCMS feature detection and retention time correction, when you have a feature table (CSV or XCMS object) with m/z and retention time values aligned across samples.
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83. ▌
    Metabolite Stability Database Retrieval · holobiomicslab

    Use when you have measured metabolites or lipids from blood samples (plasma or serum) and need to assess whether quantitative results may be compromised by pre-analytical handling.
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84. ▌
    Model Evaluation Metrics Interpretation · holobiomicslab

    Use when you have retrained or modified a neural network model (e.g., MSNovelist) to accept a different input fingerprint representation (e.
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85. ▌
    Model Performance Evaluation Roc Curves · holobiomicslab

    Use when you have a binary classification task on metabolomics data (e.g., covid_data) and need to benchmark multiple algorithms to determine which produces the highest discriminative power.
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86. ▌
    Molecular Class Annotation For Networks · holobiomicslab

    Use when after molecular formulas have been assigned to detected peaks (via CoreMS, Formularity, or equivalent) and you are constructing biochemical transformation networks where node interpretation requires understanding what chemical classes are being transformed.
    0 installs
87. ▌
    Molecular Complexity Metric Computation · holobiomicslab

    Use when you have a formula-assigned FT-ICR MS dataset (CSV or tab-delimited table with molecular formulas and mass values) and need to quantify the structural diversity, elemental stoichiometry patterns, or complexity landscape of the organic mixture.
    0 installs
88. ▌
    Molecular Graph Representation Handling · holobiomicslab

    Use when when you have molecular structure data (SMILES or molecular IDs) from chemistry databases (e.g., PubChem, HMDB) and need to feed it into a neural network architecture like TransG-Net that expects multimodal inputs combining graph-structured molecular topology with learned embeddings.
    0 installs
89. ▌
    Molecular Structure To Graph Conversion · holobiomicslab

    Use when when you have validated RDKit molecule objects from chemical databases (PubChem, HMDB) and need to generate graph-structured features for machine learning models that consume molecular topology as input.
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90. ▌
    Molecular Structure Tokenization Smiles · holobiomicslab

    Use when when you have molecular structures encoded as SMILES strings and need to incorporate them into a multi-modal language model (such as BART) that also processes mass spectra.
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91. ▌
    Msi Intensity Matrix Isotope Correction · 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).
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92. ▌
    Multi Backend Visualization Abstraction · holobiomicslab

    Use when when building a mass spectrometry visualization library that must support multiple plotting backends (matplotlib for static output, bokeh and plotly for interactive exploration) with a uniform DataFrame-based API, and where different plot kinds (spectrum, chromatogram, mobilogram, peakmap).
    0 installs
93. ▌
    Multi Branch Representation Integration · holobiomicslab

    Use when when building an end-to-end deep learning model that predicts multiple related properties from a single input (e.
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94. ▌
    Multi Organism Metabolic Data Retrieval · holobiomicslab

    Use when when you have identifiers for two organisms available in KEGG and need to compare their metabolic networks quantitatively and visually at both structural (node–edge topology) and functional (pathway role) levels for applications in drug engineering, medical science, or systems biology.
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95. ▌
    Multiclass Biomarker Quality Assessment · holobiomicslab

    Use when you have a multi-class metabolomic peak table with quality control (QC) samples included, and you need to select an optimal preprocessing workflow for downstream biomarker discovery or differential profiling.
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96. ▌
    Multiple Testing Correction Application · holobiomicslab

    Use when when performing statistical tests (e.g., t-tests, ANOVA) across many metabolites in a MultiAssayExperiment object to identify differentially abundant metabolites between sample groups.
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97. ▌
    Multistage Neural Architecture Training · holobiomicslab

    Use when you have paired mass spectra and molecular structure datasets and need to train a model that jointly understands both modalities for tasks like structure elucidation. Specifically, use it when: (1) you have large unlabeled or weakly-labeled pretraining data with both spectra and molecules;
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98. ▌
    Natural Product Database Schema Parsing · holobiomicslab

    Use when when ingesting raw data from multiple external natural-product databases with different formats, field naming conventions, and data structures.
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99. ▌
    Noise Perturbation Sensitivity Analysis · holobiomicslab

    Use when when comparing pathway analysis methods on metabolomics peak data and you need evidence that one method is more robust than another to the noise and missing peaks that are prevalent in real metabolomics experiments.
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100. ▌
     Noise Smoothing Chromatographic Signals · 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.
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