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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Kendrick Mass Calculation · holobiomicslab

   Use when you have uploaded m/z values from a high-resolution mass spectrometry analysis of a complex sample (e.g., crude oil, natural organic matter) and need to visualize homolog series trends.
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2. ▌
   Keras Model Serialization · holobiomicslab

   Use when you have downloaded pre-trained Keras model files (via get_models.sh or similar) and need to prepare them for deployment in a TensorFlow Serving environment, particularly when the downstream inference system expects .h5 serialized models with explicit input/output layer naming conventions.
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3. ▌
   La Icp Ms Image Denoising · holobiomicslab

   Use when raw LA-ICP-MS images contain isolated spike pixels (hot spots or cold spots) caused by instrumental noise, transient ablation artifacts, or detector glitches.
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4. ▌
   M Z Intensity Calibration · holobiomicslab

   Use when you have raw or processed MS spectrum data (m/z and intensity pairs) from DI-MS, ASAP-MS, or other high-throughput mass spectrometry instruments that requires automated peak detection.
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5. ▌
   Metadata Field Extraction · holobiomicslab

   Use when you have a directory of JSON-formatted annotation files and need to systematically extract a specific metadata field (such as curation status, entry identifier, or validation state) across all records.
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6. ▌
   Metadata Field Validation · holobiomicslab

   Use when you have received new or updated MassBank records (in plain-text or structured format) that must be integrated into the MassBank-data repository and you need to ensure they conform to the MassBank format specification before acceptance.
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7. ▌
   Mibig Metadata Extraction · holobiomicslab

   Use when when you need to audit, inventory, or report on the curation state of MIBiG entries; when cluster.status values must be validated or aggregated for quality control; when building a status index to support data governance or release workflows.
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8. ▌
   Module Dependency Mapping · holobiomicslab

   Use when you need to understand or document the structural organization of an object-oriented codebase—specifically when developers require a map of which modules depend on others, where extension points (abstract classes, interfaces, factory patterns) exist, or when preparing to extend or refactor.
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9. ▌
   Mrm Data Format Ingestion · holobiomicslab

   Use when you have raw MRM lipidomics export files in vendor-specific formats (e.g., TSV or CSV from a mass spectrometry instrument) and need to convert them into a standardized tabular format before performing lipid identification, statistical analysis, or visualization.
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10. ▌
    Network Graph Pca Overlay · holobiomicslab

    Use when you have a sparse network graph generated by GLASSO and corresponding PCA scores from the same system, and you need to identify which regions or clusters of the network exhibit strong low-dimensional structure.
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11. ▌
    Network Proximity Scoring · holobiomicslab

    Use when you have (1) metabolomic hits (DAMs or enriched metabolites) mapped to seed genes, (2) a protein–protein or gene interaction network (e.g., STRING), and (3) a set of candidate disease genes that need ranking by their functional proximity to metabolomic evidence.
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12. ▌
    Overlapping Ion Detection · holobiomicslab

    Use when when annotating matrix-related ions in MSI datasets where two or more ions share identical or near-identical m/z values (isobaric ions) or exhibit overlapping spatial distributions across imaging pixels.
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13. ▌
    Pep8 Standard Enforcement · holobiomicslab

    Use when preparing code for contribution to a Python project that mandates PEP8 compliance, or when setting up pre-commit quality gates for a codebase.
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14. ▌
    Prediction Error Analysis · holobiomicslab

    Use when when you have trained multiple machine learning regressors on the same prediction task (e.
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15. ▌
    Proforma Notation Parsing · holobiomicslab

    Use when when peptide identifications from a search engine (MaxQuant, MSGFPlus, Sage, etc.) contain custom or engine-specific modification notation that must be converted to a standardized format before rescoring, or when different search engines use incompatible modification label schemes that.
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16. ▌
    Python Module Integration · holobiomicslab

    Use when when you have developed or obtained a new Python package that encapsulates domain-specific computational logic (e.
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17. ▌
    Python R Interoperability · holobiomicslab

    Use when when a Shiny R application needs to use Python libraries that lack R equivalents or are more mature in Python (e.g., Kaleido for plot export), and users should not need to manually configure Python environments.
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18. ▌
    R Package Function Export · holobiomicslab

    Use when you have built a reusable workflow function (e.g., a Shiny app launcher, automated analysis routine) within an R package and need to make it available to package users.
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19. ▌
    Raw Spectral Data Reading · holobiomicslab

    Use when you have Thermo Orbitrap .raw files and need to extract specific spectral features (base-peak m/z, intensity values, chromatographic traces, scan-level metadata) for downstream statistical analysis or visualization in R. Use this skill when you want to avoid lossy format conversion (e.
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20. ▌
    Rendering Speed Profiling · holobiomicslab

    Use when when you have implemented the same visualization (e.g., chromatogram, spectrum, peakmap, mobilogram) across multiple plotting backends in pyOpenMS-viz and need to determine which backend minimizes rendering latency.
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21. ▌
    REST API Endpoint Routing · holobiomicslab

    Use when your input is a raw query string containing a chemical compound identifier and structural representation (e.g. tab-delimited compound ID + structure), and you need to submit it to the ClassyFire API for automatic structure-based classification.
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22. ▌
    Retention Time Clustering · holobiomicslab

    Use when you have an XCMS CentWave feature extraction output table containing multiple features with near-identical m/z values and retention times (e.
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23. ▌
    Runtime Output Validation · holobiomicslab

    Use when after invoking a Nextflow workflow via `make run` or equivalent command, to confirm the workflow executed without errors and generated expected output files.
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24. ▌
    Smiles Format Preparation · holobiomicslab

    Use when you have molecular structures in raw or unstructured form and need to submit them to CypReact or similar command-line chemistry tools that accept CSV input.
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25. ▌
    Smiles String Preparation · holobiomicslab

    Use when you have a target molecule (e.g., acetaminophen, a drug candidate, or a xenobiotic) whose structure you need to encode for metabolite prediction, reaction rule matching, or other structure-based cheminformatics workflow.
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26. ▌
    Software Tool Enumeration · holobiomicslab

    Use when a software package claims to bundle or install a specific number of tools (documented or approximate) but the tool names, versions, and sources are not enumerated in the primary README or documentation.
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27. ▌
    Spatial Feature Embedding · holobiomicslab

    Use when when analyzing imaging mass spectrometry datasets where you need to reduce high-dimensional peak intensity features while preserving spatial structure, and when automatic peak picking and marker ion identification are required.
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28. ▌
    Spectral Library Indexing · holobiomicslab

    Use when you have large spectral libraries (thousands to millions of spectra) and need to search query spectra against them for peptide identification with tolerance for post-translational modifications.
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29. ▌
    Spectral Signal Detection · holobiomicslab

    Use when you have mzML mass spectrometry data and a list of predicted candidate metabolites (with known mass-to-charge ratios and retention times) for a drug of interest, and you need to determine which candidates actually appear in the observed spectra rather than treating all predictions as.
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30. ▌
    Threshold Based Filtering · holobiomicslab

    Use when after computing pairwise similarity scores between query molecular embeddings and a reference database, apply this skill when you need to distinguish high-confidence candidate matches from spurious matches.
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31. ▌
    Training Dataset Assembly · holobiomicslab

    Use when when you have a large list of SMILES strings but lack corresponding experimental mass spectra, and you need to generate 30,000+ training pairs to train a deep learning model for molecular structure prediction.
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32. ▌
    Virtual Screening Ranking · holobiomicslab

    Use when you have a library of natural product compounds (encoded as SMILES strings) and wish to rank them by predicted bioactivity or fitness for a downstream task.
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33. ▌
    Xcms Parameter Estimation · holobiomicslab

    Use when you have raw untargeted metabolomics data (at least 3 samples in mzML, mzXML, or CDF format) from qTOF, orbitrap, or Fourier transform ion cyclotron resonance mass analyzers and need to obtain optimized XCMS processing parameters tailored to your specific instrument and dataset rather than.
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34. ▌
    Paga Graph Abstraction · holobiomicslab

    Use when you have clustered single-cell RNA-seq data (via Leiden, Louvain, or equivalent) and a k-nearest neighbor graph computed in PCA space, and you want to abstract cell-level connectivity into cluster-level connectivity to infer developmental trajectories, lineage relationships, or.
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35. ▌
    Msconvert Tool Configuration · holobiomicslab

    Use when you have vendor-specific raw mass spectrometry data files (e.g., from Orbitrap, Q-TOF, or other MS instruments) and need to feed them into IsoFusion or other tools that require MS1 format as input.
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36. ▌
    Baseline Comparison Analysis · holobiomicslab

    Use when when you have trained a candidate model (e.g., an ensemble, a new architecture) and need to demonstrate its advantage over published or reference implementations on the same test data.
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37. ▌
    Gc Ms Spectral Deconvolution · holobiomicslab

    Use when you have raw GC-MS data (in netCDF or vendor format) containing overlapping chromatographic peaks from complex mixtures where individual compound spectra cannot be resolved by simple peak picking.
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38. ▌
    Gc Ms Spectral Preprocessing · holobiomicslab

    Use when you have raw GC-MS data files containing overlapped peaks (unresolved components with coeluting retention times) and need to predict pure mass spectra for each individual component using a Transformer-based model.
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39. ▌
    Metadata Coldata Integration · holobiomicslab

    Use when when you have generated a feature abundance matrix from mzrtsim() peak list simulation with known sample-level attributes (condition assignments, batch labels, sample identifiers) and need to package this into a SummarizedExperiment object for Bioconductor-compatible analysis pipelines.
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40. ▌
    Model Checkpoint Persistence · holobiomicslab

    Use when training a Transformer or neural network model on a large dataset (e.g., 80,000+ training samples) where validation performance is monitored to prevent overfitting, and you need to halt training early or recover the -performing model checkpoint without re-executing the entire training loop.
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41. ▌
    Ms Spectral Library Matching · holobiomicslab

    Use when when you have a GC-MS dataset (CSV with columns: Component.RT, Component.Area, Base.Peak.MZ, File.Name, Compound.Name, Match.Factor) and a known set of target chemicals you wish to locate and extract with their spectral match quality and quantitation.
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42. ▌
    Noise Level Parameter Tuning · holobiomicslab

    Use when when you have an aligned GCIMS dataset and need to configure the findPeaks function with CWT algorithm to detect peaks across retention time and drift time dimensions.
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43. ▌
    Pareto Scaling Normalization · holobiomicslab

    Use when you have peak intensity vectors from LC/GC-MS experiments with corresponding QC (quality control) sample measurements, and you need to correct for batch effects—especially when QC samples show systematic shifts in peak heights across analytical batches.
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44. ▌
    Similarity Score Computation · holobiomicslab

    Use when when you have a query electron ionization mass spectrum (m/z and intensity pairs) and need to identify the most similar spectra from an MSP-formatted spectral library.
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45. ▌
    Spectral Metadata Extraction · holobiomicslab

    Use when after loading an MSP spectral library file into memory using mssearchr's MSP parser, when you need to verify that each spectrum record contains complete and valid metadata (precursor m/z values, peak lists, header annotations) before writing the parsed spectra to a new MSP file or.
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46. ▌
    Spectral Peak Shape Modeling · holobiomicslab

    Use when when generating synthetic LC/GC-MS .mzML files from MoNA or HMDB spectral records where you need to compute absolute ground-truth maximum intensity (sim_ins) for each peak while accounting for chromatographic band broadening, peak tailing, and retention-time dispersion.
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47. ▌
    Alignment Quality Assessment · holobiomicslab

    Use when after retention time and m/z-based clustering have been applied to group features across samples in a multi-sample metabolomics study.
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48. ▌
    Analog Search Result Routing · holobiomicslab

    Use when after MS2Query has ranked and scored library matches against query spectra, when you need to apply different confidence thresholds, interpretation strategies, or downstream workflows depending on whether the result is an exact match (precursor m/z difference ≈ 0) or a chemical analog.
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49. ▌
    Candidate Metabolite Ranking · holobiomicslab

    Use when when you have generated a set of predicted metabolite structures from BioTransformer's metabolism prediction engine and need to assign identity to observed compounds from LC-MS/MS, spectral, or chromatographic experiments.
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50. ▌
    Chemical Formula Enumeration · holobiomicslab

    Use when you have an unknown MS/MS spectrum with a measured precursor m/z and want to generate a list of plausible chemical formula–adduct pairs to rank or filter downstream.
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51. ▌
    CI CD Pipeline Orchestration · holobiomicslab

    Use when you need to automate testing and quality checks on code changes—specifically when pull requests or commits are made to a repository and you want to verify that builds succeed, test suites pass, and code quality metrics meet project standards before merging.
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52. ▌
    Cloud Compatible File Output · holobiomicslab

    Use when after feature clustering and drift correction (Gravity and Blueshift outputs) are complete and you need to produce a final, validated feature table ready for storage, archival, or downstream analysis.
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53. ▌
    Conditional Dispatch Routing · holobiomicslab

    Use when you have received a peak/feature table from an unknown or variable upstream peak-picking tool and need to ingest it into LipidMatch or a similar unified workflow. The input file format, column naming, or metadata structure is tool-specific (e.
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54. ▌
    CSV To Dictionary Conversion · holobiomicslab

    Use when you have a CSV file containing molecule definitions (chemical formula, m/z, intensity, retention time, or other peak properties) and need to prepare it for SMITER's simulation workflow.
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55. ▌
    Electronic Noise Ion Removal · holobiomicslab

    Use when working with raw MS/MS spectra that contain ions with repeated (identical) intensity values—a hallmark of electronic noise rather than true metabolite fragments.
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56. ▌
    Energy Based Formula Scoring · holobiomicslab

    Use when you have an unknown MS/MS spectrum (precursor m/z and fragment peak list) and a set of candidate molecular formulae, and you need to rank them by likelihood without access to a spectrum database or precomputed fragmentation trees.
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57. ▌
    Energy Based Model Inference · holobiomicslab

    Use when when you have an unknown MS/MS spectrum (m/z and intensity pairs) and need to assign a chemical formula and ionization adduct to the precursor mass, particularly when spectrum database lookups are unavailable or when you want to exploit learned patterns in fragmentation rather than.
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58. ▌
    Exact Mass Database Matching · holobiomicslab

    Use when after feature detection and alignment on raw MS data, when you have a list of unknown feature m/z values and need to assign them to known xenobiotic metabolites or their predicted biotransformation products.
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59. ▌
    False Discovery Rate Control · holobiomicslab

    Use when you have generated candidate peptide-spectrum matches from a spectral library search (especially open modification searches using cascade strategies) and need to assign statistical confidence to those matches. Use it whenever the scoring metric (e.
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60. ▌
    Feature Annotation Filtering · holobiomicslab

    Use when you have a feature list with assigned molecular formulas and m/z values from non-target HRMS analysis, and you need to identify and rank potential PFAS compounds among thousands of detected features.
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61. ▌
    Filter Output Interpretation · holobiomicslab

    Use when after applying a filter function (filter_mispicked_ions(), filter_group(), filter_cv(), filter_insource_ions()) to an mpactr object, use this skill to inspect and document which features were retained versus removed.
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62. ▌
    Fragmentation Motif Learning · holobiomicslab

    Use when you have preprocessed mass spectrometry fragmentation data (neutral losses and fragment masses extracted and noise-filtered) and want to discover hidden structural motifs across a spectral dataset in an unsupervised manner.
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63. ▌
    Gnps Library Format Assembly · holobiomicslab

    Use when you have extracted MS1 and MS2 scans (in mzML/mzXML format) from raw chromatogram files and possess user-provided metadata (retention time, m/z, compound name, molecular weight, annotation fields) that must be combined into a single structured library entry suitable for spectral library.
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64. ▌
    Gnps Workflow Identification · holobiomicslab

    Use when you have downloaded a GNPS molecular networking job archive and need to extract its contents (spectra.mgf, molecular_families.tsv, annotations.tsv, file_mappings) but do not know which GNPS workflow version produced it, preventing correct file naming and downstream computational analysis.
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65. ▌
    Heatmap Visualization Design · holobiomicslab

    Use when after training a DeepMSProfiler model and generating per-sample predictions: when you need to display Pearson or Spearman correlation coefficients between individual metabolite signals and disease class labels in a matrix form suitable for publication or exploratory review of.
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66. ▌
    Homologous Series Clustering · holobiomicslab

    Use when you have a feature list (m/z, retention time, intensity) from HRMS data and want to identify potential PFAS homologous series for prioritization.
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67. ▌
    Installation Troubleshooting · holobiomicslab

    Use when when setting up matchms for the first time in a new environment, after upgrading Python or conda, when switching between package managers (pip vs conda), or when distributing matchms to end users to confirm functionality across supported installation channels.
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68. ▌
    Instrumental Drift Detection · holobiomicslab

    Use when you have a time-series of repeated QCpool (pooled quality control) injections measured at regular intervals during one or more LC-MS/MS sequences, exported from Sciex Multiquant software (v3.0.
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69. ▌
    Intensity Frequency Analysis · holobiomicslab

    Use when you have an MS/MS peak list and need to remove electronic noise—specifically when you observe suspiciously identical intensity values repeated across multiple peaks in a single spectrum, which is characteristic of instrument-generated artifacts rather than genuine analyte signals.
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70. ▌
    Knime Workflow Orchestration · holobiomicslab

    Use when you have raw LC-MS data (mzML, NetCDF) from multiple runs that require sequential feature detection, alignment, quantification, and optional filtering (e.g., blank exclusion, QC reproducibility, retention-time outlier removal) before spatial mapping or annotation.
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71. ▌
    Library Integration Workflow · holobiomicslab

    Use when you have custom lipid entries (e.g., synthetic lipids, rare natural variants, or isotopically labeled standards) not covered by LipidMatch's default in-silico library, and you want to include them as matching candidates in your UHPLC-HRMS/MS fragment m/z matching workflow without modifying.
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72. ▌
    Linux Command Line Execution · holobiomicslab

    Use when you have vendor-specific raw mass spectrometry data (ThermoFisher .raw, Agilent .
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73. ▌
    Lipid A Structure Annotation · holobiomicslab

    Use when when you have high-resolution tandem mass spectrometry (MS2) data in .ms2 format and need to identify and annotate lipid A structures at scale.
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74. ▌
    Lipid Identification Scoring · holobiomicslab

    Use when after peak picking (MZmine, XCMS, MS-DIAL, or Compound Discoverer output) and candidate retrieval, when you have experimental fragment m/z values and multiple candidate lipid species from the in-silico library.
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75. ▌
    Lipid Species Identification · holobiomicslab

    Use when you have centroid-mode LC–MS AIF chromatograms processed by xcms and RamClustR (or equivalent), a feature table with m/z and retention time coordinates, and you need to resolve individual lipid species identities with confidence scores and fragmentation evidence.
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76. ▌
    M Z Alignment Across Samples · holobiomicslab

    Use when you have extracted mass tracks (EICs) from multiple LC-MS samples at 0.001 amu resolution and need to construct a sample-agnostic m/z reference frame.
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77. ▌
    Mass Feature To Node Mapping · holobiomicslab

    Use when you have an untargeted metabolomics feature table with m/z values, retention times, and intensity measurements, a metabolic network representation with compound nodes and chemical formulas, and you want to infer functional pathway activity directly from features without performing.
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78. ▌
    Massql Query Language Syntax · holobiomicslab

    Use when you need to search for specific mass spectrometry patterns (e.g., precursor ion m/z, product ion presence, retention time windows, intensity constraints, neutral loss patterns) across one or more mzML files.
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79. ▌
    Matplotlib Heatmap Rendering · holobiomicslab

    Use when when you have a confusion matrix (predicted vs. ground-truth labels) or similarity matrix (pairwise scores between spectra) and need to communicate classification accuracy or chemical similarity patterns through a visual heatmap.
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80. ▌
    Metabolite Candidate Ranking · holobiomicslab

    Use when you have an untargeted mass spectrometry spectrum (MS/MS data) and a set of candidate molecules from PubChem or similar databases, and you need to rank candidates by likelihood of being the true molecular annotation.
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81. ▌
    Metabolite Ion Consolidation · holobiomicslab

    Use when after chromatographic peak detection in LC-MS data, when you have hundreds or thousands of features and need to consolidate ions presumed to originate from the same metabolite.
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82. ▌
    Metabolomic Feature Matching · holobiomicslab

    Use when you have two LC-MS feature tables (each with m/z, retention time, and intensity columns) from separate metabolomic experiments or replicates, and you need to establish which features in dataset A correspond to which features in dataset B to enable comparative or longitudinal analysis.
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83. ▌
    Metabolomics Data Formatting · holobiomicslab

    Use when after running feature clustering (Gravity) or drift correction (Blueshift) on LCMS data, when you have a processed feature table and need to standardize its structure, validate metadata completeness, enforce missing-value thresholds, and generate a QC report documenting pass/fail status.
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84. ▌
    Metabolomics Tool Deployment · holobiomicslab

    Use when you have a Galaxy installation (specifically Galaxy Master branch commit c429777c93680dcee449fe410f5360afbe673758 or compatible) and need to add metabolomics analysis capabilities including tools for XCMS integration, mass spectrometry file reading (via MSFileReader), and metabolite.
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85. ▌
    Metadata Field Normalization · holobiomicslab

    Use when immediately after importing raw mass spectrometry data from mzML, mzXML, msp, MGF, or JSON formats into matchms.
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86. ▌
    Molecular Formula Assignment · holobiomicslab

    Use when you have acquired MS/MS spectra (in MGF format with required fields: TITLE, PRECURSOR_MZ, PRECURSOR_TYPE, COLLISION_ENERGY) from known or unknown compounds and need to predict their molecular formulas with ranked candidates and confidence scores.
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87. ▌
    Molecular Formula Validation · holobiomicslab

    Use when when you have a feature list from HRMS with tentatively assigned molecular formulas (from in silico tools or databases) and need to assess formula plausibility before applying downstream PFAS-specific filters.
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88. ▌
    Ms Feature Tree Construction · holobiomicslab

    Use when you have untargeted LC-MS/MS metabolomic data (peak-detected .mzXML/.mzML/.mzDATA files processed through MZmine2) and need to relate MS1 features by chemical similarity rather than sequence homology.
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89. ▌
    Ms Ms Spectrum Preprocessing · holobiomicslab

    Use when you have raw or semi-processed MS/MS spectral data from bottom-up tandem mass spectrometry experiments (data-dependent acquisition) that you intend to input to de novo peptide sequencing tools like Casanovo.
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90. ▌
    Multi Class Label Assignment · holobiomicslab

    Use when you have raw LC-MS metabolomics data from multiple disease groups and need to classify new or existing samples into discrete disease categories.
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91. ▌
    Multi Omics Data Integration · holobiomicslab

    Use when when you have matched transcriptomics (RNA-seq read counts), intracellular metabolomics (LC-MS abundance data), and extracellular flux measurements (YSI bioanalyzer or similar) from multiple biological samples or cell lines, and you need to determine whether differences in metabolic enzyme.
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92. ▌
    Multiblock Pls Model Fitting · holobiomicslab

    Use when you have split multi-assay LC-MS intensity data into training (90%) and test (10%) subsets with assay-specific column prefixes, and you need to fit a discriminant or regression model that respects the block structure (separate assays) while jointly predicting a phenotypic outcome (e.
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93. ▌
    Mzml Spectral Format Parsing · holobiomicslab

    Use when you have mzML-format raw data files (from any mass spectrometry vendor or conversion tool) and need to ingest them into MS-DIAL version 5 or later for untargeted metabolomics or lipidomics analysis.
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94. ▌
    Network Node Label Spreading · holobiomicslab

    Use when you have an untargeted metabolomics dataset with a two-layer network topology already constructed (one layer representing biochemical knowledge/pathways, the other representing data-driven MS2 similarity), seed metabolites with reliable annotations from database matching or curation, and.
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95. ▌
    Pairwise Spectral Comparison · holobiomicslab

    Use when you have a collection of preprocessed mass spectra (in mzML, mzXML, msp, MGF, or JSON format) and need to quantify similarity relationships across all pairs—for instance, to identify redundant spectra in a library, cluster related compounds, or perform spectral library searches.
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96. ▌
    Pairwise Spectrum Comparison · holobiomicslab

    Use when you have a collection of cleaned mass spectrometry spectra (in mzML, mzXML, msp, MGF, or JSON format) and need to identify spectral similarities, find related compounds, or generate a comprehensive similarity matrix for downstream analysis such as spectral library matching or clustering.
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97. ▌
    Peak Filtering Noise Removal · holobiomicslab

    Use when you have raw MS/MS spectra (in formats like mzML, json, mgf, msp, mzxml) that contain background noise or numerous low-intensity peaks before running MS2Query library matching.
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98. ▌
    Peak Intensity Normalization · holobiomicslab

    Use when you have raw MS/MS spectral peak lists with absolute intensity values and need to compare spectra using entropy similarity, dot product, or other distance metrics.
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99. ▌
    Peak Recovery Post Filtering · holobiomicslab

    Use when after applying cluster-based filtering with quasi-molecular adduct constraints and frequency thresholds on LC-MS feature candidates, when some peaks have been entirely removed from the candidate pool and you want to prevent loss of true metabolites that failed to meet filtering criteria.
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100. ▌
     Phylogenetic Tree Validation · holobiomicslab

     Use when after generating a Chemical Feature Tree from q2-qemistree (or any tree artifact) and before using it for alpha-diversity or beta-diversity phylogenetic analyses.
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