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HolobiomicsLab

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1. ▌
   Reference Peak Matching Retention Time Alignment 2 · holobiomicslab

   Use when you have training LC-HRMS chromatograms (rt × m/z matrix format) from which you have already extracted peak candidates using smoothing and gradient-descent peak detection, and you possess a curated reference list of isolated single chromatographic peaks (ground truth).
   0 installs
2. ▌
   Reproducibility Statistic Computation Rank Based 2 · holobiomicslab

   Use when you have high-dimensional replicate experiment data (metabolomics, proteomics, or genomics) with multiple biological or technical replicates per sample, and you need to assess which features are reproducible across replicates and which sample pairs show consistent reproducibility patterns.
   0 installs
3. ▌
   Dimension Scale Linking And Cross Group Indexing 2 · holobiomicslab

   Use when when exporting quantified MSI data as HDF5 containers following the Cardinal::HDF5 layout convention, and you need to establish bidirectional indexing between intensity data (feature-by-pixel matrix) and metadata groups (featureData, pixelData).
   2 installs
4. ▌
   Single Cell Spatial Metabolomics Data Processing 2 · holobiomicslab

   Use when you have raw IMC and SIMS image data from the same tissue region(s) and need to: (1) register the two modalities spatially, (2) segment individual cells across both images, (3) extract per-cell protein and metabolite intensity vectors, and (4) prepare the data for downstream joint analysis.
   0 installs
5. ▌
   CI CD Workflow Adaptation To Organization Standards 2 · holobiomicslab

   Use when when a Python package is being relocated to a new GitHub organization (e.
   2 installs
6. ▌
   Collision Cross Section Measurement Quality Control 2 · holobiomicslab

   Use when you have IM-MS lipidomics data from samples spiked with U13C-labeled internal standards (fully labeled yeast extract) and you need to quantify whether measured CCS values deviate systematically from theoretical values, or when you want to correct CCS measurements before downstream lipid.
   2 installs
7. ▌
   Feature Network Construction From Mass Spectrometry 2 · holobiomicslab

   Use when you have a preprocessed feature table (tab-delimited: feature ID, m/z, retention time, intensity columns) from LC-MS data and need to annotate which observed features represent the same underlying compound via isotope or adduct relationships.
   2 installs
8. ▌
   Metabolite Identification From Transformation Rules 2 · holobiomicslab

   Use when when you have a small-molecule structure (SMILES, MOL, or SDF format) and need to identify probable metabolites or degradation products in a specific biological compartment (e.g., soil/aquatic microbiota, mammalian liver, or gut microbiota).
   0 installs
9. ▌
   Principal Component Extraction From Pathway Subsets 2 · holobiomicslab

   Use when you have a log2-normalized, zero-mean and unit-variance standardized intensity matrix of metabolite features (rows=metabolites, columns=samples) and need to compute a single activity score per pathway that reflects the coordinated expression behavior of all metabolites assigned to that.
   0 installs
10. ▌
    Scalability Extrapolation And Throughput Estimation 2 · holobiomicslab

    Use when you have a new or modified LC-MS data processing tool and need to determine whether it can handle production-scale sample cohorts (50–100+ samples) on modest hardware (single-core CPU, ≤16 GB RAM).
    2 installs
11. ▌
    Smarts Pattern Matching For Chemical Transformation 2 · holobiomicslab

    Use when when you have seed metabolite structures (SMILES or MOL format) from metabolomics data and a curated biotransformation rule database (each rule specifying reactant SMARTS, product SMARTS, and transformation type), and you need to systematically enumerate plausible biotransformation.
    2 installs
12. ▌
    Structural Similarity Calculation Fingerprint Based 2 · holobiomicslab

    Use when you have a set of compounds (e.g., novel NPS analogues in an evaluation dataset) and need to classify them as structurally similar to or divergent from a reference set (e.g., training compounds).
    0 installs
13. ▌
    Spectral Data Compression By Frame And Mobility 2 · holobiomicslab

    Use when you have raw IM-MS data in Agilent MassHunter (.d) or UIMF format from drift tube (DT) or SLIM instruments, and you need to reduce data volume while preserving signal integrity for subsequent HRdm demultiplexing and peak deconvolution.
    0 installs
14. ▌
    Probabilistic Classification Network Construction 2 · holobiomicslab

    Use when when you have raw mass spectrometry imaging data tensors and need to build a trainable deep-learning classifier that outputs class probabilities (tumor vs. non-tumor) without preprocessing or manual peak detection.
    0 installs
15. ▌
    Annotation Accuracy And Coverage Metrics Computation 2 · holobiomicslab

    Use when after executing an end-to-end structure annotation pipeline (such as BAM) on a validation dataset with known reference annotations.
    0 installs
16. ▌
    Bayesian Optimization Acquisition Function Selection 2 · holobiomicslab

    Use when after fitting a Gaussian Process regression model to prior LC-MS gradient evaluations (where gradients are encoded as input and separation efficiency is output), use this skill to decide which candidate gradient to test next.
    2 installs
17. ▌
    Metabolite Phenotype Association Partial Correlation 2 · holobiomicslab

    Use when you have a SummarizedExperiment object containing NMR or MS metabolomic data with aligned phenotype information (BMI, disease status, age, gender), and you need to identify metabolites associated with a continuous or categorical outcome while controlling for known confounders that might.
    0 installs
18. ▌
    One Hot Encoding Categorical Chromatography Features 2 · holobiomicslab

    Use when you have raw HPLC column metadata containing categorical fields (e.g., column manufacturer 'Waters', USP type 'L1', solvent identities 'H2O'/'MeOH'/'ACN') that must be converted into numerical representations before featurization for a machine learning pipeline.
    0 installs
19. ▌
    Precision Recall Optimization In Spectral Annotation 2 · holobiomicslab

    Use when you have extracted fragmentation patterns from a collection of MS/MS spectra (using mineMS2) and have partitioned spectra into components via GNPS molecular networking (e.g., connected components, cliques, or high-similarity pairs with cosine > threshold).
    0 installs
20. ▌
    Mass Spectrometry Feature Similarity Modeling 2 · holobiomicslab

    Use when when you have an untargeted metabolomics dataset with MS2 fragmentation spectra and need to annotate metabolites beyond what reference databases alone provide.
    0 installs
21. ▌
    Data Quality Assessment From Molecular Descriptors 2 · holobiomicslab

    Use when processing spectral datasets from open mass spectra libraries (OMSLs) where structural identifiers and ionization metadata are incomplete or inconsistent.
    0 installs
22. ▌
    Spectrum Document Conversion Peak Loss Representation 2 · holobiomicslab

    Use when when preparing MS/MS spectral data for training word-embedding models (Word2Vec, Skip-gram, CBOW) that will learn relationships between fragment ions and neutral losses.
    2 installs
23. ▌
    Automated Peak Detection Without Conventional Picking 2 · holobiomicslab

    Use when you have a two-dimensional GC–MS or LC–MS dataset (m/z vs retention time) and need to identify discriminative analyte features without relying on conventional peak picking algorithms. This is especially valuable when analyzing complex, low-abundance samples (e.
    0 installs
24. ▌
    Comparative Algorithm Benchmarking For Peak Detection 2 · holobiomicslab

    Use when you have developed or adapted a peak detection method for chromatography–mass spectrometry and need to validate its reliability against an established baseline on the same raw GC–MS dataset. Specifically when: (1) the input is raw GC–MS data in m/z vs retention time format;
    2 installs
25. ▌
    Machine Learning Model Training With Cross Validation 2 · holobiomicslab

    Use when when you have a labeled peak quality matrix (with known pass/fail labels), need to objectively compare performance across multiple classification algorithms (e.
    0 installs
26. ▌
    Peak Evaluation Metrics Cselectivity Snr Gaussian Fit 2 · holobiomicslab

    Use when after scipy.signal.find_peaks has identified candidate peaks on a composite mass track segment, evaluate each peak to decide whether to retain it in the final feature table.
    0 installs
27. ▌
    Ppb Level Marker Detection And Sensitivity Assessment 2 · holobiomicslab

    Use when you have raw GC–MS or LC–MS data in two-dimensional m/z vs retention time format and need to identify marker features at parts-per-billion sensitivity without relying on conventional peak picking.
    0 installs
28. ▌
    Relative Standard Deviation Calculation Qc Replicates 2 · holobiomicslab

    Use when you have a peak table from XCMS preprocessing with intensity measurements for the same set of metabolites across multiple QC replicate injections (samples marked SampleType='LQC'), and you need to filter out EICs with poor reproducibility before evaluating peak quality or training a.
    1 install
29. ▌
    Spectral Dataset Partitioning And Train Test Curation 2 · holobiomicslab

    Use when when you have a pre-cleaned spectral library (e.g., GNPS, MoNA, or MTBLS1572) with an existing training/test boundary established by prior work (e.g., MSBERT), and you need to report model performance with uncertainty quantification across multiple random partitions.
    0 installs
30. ▌
    Multi Mode Filter Application High Dimensional Data 2 · holobiomicslab

    Use when you have high-dimensional biological data (e.
    0 installs
31. ▌
    Word2vec Vocabulary Matching And Unknown Peak Handling 2 · holobiomicslab

    Use when converting MS/MS spectra into Spec2Vec embeddings using a pre-trained Word2Vec model that was trained on reference data (e.g., a subset of GNPS or MassBank).
    0 installs
32. ▌
    Categorical Numerical Feature Concatenation For Graphs 2 · holobiomicslab

    Use when when preparing heterogeneous column-metadata inputs for a graph transformer model that operates on molecular graphs. Specifically: (1) you have both categorical metadata (e.
    2 installs
33. ▌
    Chromatographic Peak Detection With Prominence Control 2 · holobiomicslab

    Use when after constructing baseline-corrected mass tracks (either composite across samples or per-sample) when you need to identify individual chromatographic peaks for feature extraction in LC-MS or GC-MS metabolomics workflows.
    0 installs
34. ▌
    Connected Component Decomposition In Mass Spectrometry 2 · holobiomicslab

    Use when you have a feature list from LC-MS preprocessing (e.g., asari output) and have already identified all pairwise feature matches to isotope and adduct patterns. Apply this skill when you need to separate feature matches into disjoint empirical compounds—i.
    2 installs
35. ▌
    Metabolomics Functional Prediction Workflow Validation 2 · holobiomicslab

    Use when a Python-based metabolomics analysis package has been relocated to a new GitHub organization (e.g., metabolomics-cloud) and you need to confirm that the migration preserved package integrity, installation, and runtime correctness.
    0 installs
36. ▌
    Molecular Geometry Neural Network Potential Evaluation 2 · holobiomicslab

    Use when after RDKit has generated multiple conformations for a molecule in an SDF or XYZ format, and you need to reduce the conformational ensemble to a tractable size (by energy-based ranking) before submitting to expensive quantum-chemical calculations (e.g., QUICK).
    0 installs
37. ▌
    Peak Quality Assessment By Selectivity And Snr Metrics 2 · holobiomicslab

    Use when after elution peaks have been detected on composite mass tracks using local maxima and prominence thresholds, and before mapping detected features back to individual samples or performing pre-annotation.
    0 installs
38. ▌
    Separation Efficiency Calculation From Retention Times 2 · holobiomicslab

    Use when you have extracted retention times from MS1 spectra for top signals in a single LC-MS/MS run and need to evaluate whether that gradient's separation performance is sufficient, or when you are building the objective function for an iterative gradient optimization loop where each candidate.
    0 installs
39. ▌
    Biotransformation Candidate Integration With Networking 2 · holobiomicslab

    Use when you have output from a biotransformation rules module (candidate transformed structures linked to anchor molecules) and untargeted MS/MS spectral data, and you want to identify molecular families and annotate features with predicted structures by leveraging spectral similarity and network.
    0 installs
40. ▌
    Biotransformation Prediction Across Microbiota Contexts 2 · holobiomicslab

    Use when you have one or more small-molecule chemical structures (as SMILES, MOL, or SDF) and need to systematically explore their fate across mammalian biotransformation, human gut microbial degradation, or environmental (soil/aquatic) microbial degradation.
    2 installs
41. ▌
    Ion Tree Structure Optimization And Trunk Establishment 2 · holobiomicslab

    Use when after you have partitioned a feature network into connected subnetworks (each containing ion features linked by isotope or adduct mass differences).
    0 installs
42. ▌
    Sample Batch Balancing Across Classification Dimensions 2 · holobiomicslab

    Use when designing multi-batch LC/GC-MS experiments where samples belong to multiple groups or conditions and you need to ensure that each injection plate receives a balanced representation of all groups.
    0 installs
43. ▌
    Species Authentication Classification Evaluation 2 · holobiomicslab

    Use when when you have high-throughput mass spectrometry data (DI-MS, ASAP-MS, LDI-MS, or other ambient ionization formats) from unknown biological samples and need to determine their species identity against a curated reference database.
    2 installs
44. ▌
    Raw Spectral Data Input Handling Without Peak Picking 2 · holobiomicslab

    Use when when you have raw mass spectrometry imaging data (full m/z profiles with intensity arrays) and want to classify spatial regions (e.
    0 installs
45. ▌
    Retention Time Projection Across Chromatographic Methods 2 · holobiomicslab

    Use when when you have retention times measured on one chromatographic method and need to predict or map them to another method with minimal or no overlap in measured molecules.
    0 installs
46. ▌
    Tree Structure Optimization For Metabolite Deconvolution 2 · holobiomicslab

    Use when you have a connected subnetwork of LC-MS features that matched isotope or adduct patterns, and you need to establish a canonical tree representation with a single neutral mass assignment.
    0 installs
47. ▌
    Mass Spectrometry Instrument Format Compatibility 2 · holobiomicslab

    Use when you have raw mass spectrometry data from an instrument not yet validated in your pipeline (e.
    2 installs
48. ▌
    Species Candidate Ranking From Spectral Alignment 2 · holobiomicslab

    Use when you have an unknown sample spectrum (m/z peaks and intensities from DI-MS, ASAP-MS, or other high-throughput mass spectrometry modalities) and a reference species database of known spectra, and you need to identify the most likely species or authenticate the sample by ranking how well each.
    0 installs
49. ▌
    Mobility Dimension Interpolation For Peak Resolution 2 · holobiomicslab

    Use when working with raw multiplexed IM-MS data (UIMF or Agilent MassHunter .
    0 installs
50. ▌
    Plant Species Authentication Via Mass Spectrometry 2 · holobiomicslab

    Use when when you have mass spectrometry raw data (DI-MS or ASAP-MS format) from plant samples that are easily confused due to morphological similarity, or when you need to verify or authenticate the species identity of a plant material against a reference database.
    0 installs
51. ▌
    Computational Efficiency Single Pass Vs Repeated Detecti 2 · holobiomicslab

    Use when when processing aligned LC-MS data across multiple samples where the computational bottleneck is repeated peak-detection algorithm calls (one per sample per m/z value). Typical scenario: >10 samples with >1000 m/z values each, where N individual find_peaks invocations dominate runtime.
    0 installs
52. ▌
    Image Processing On Two Dimensional Mass Spectrometry Ma 2 · holobiomicslab

    Use when when you have raw GC–MS data in two-dimensional m/z × retention time format (NetCDF or proprietary binary) and need to identify marker features across aroma or breath samples at parts-per-billion concentration levels, particularly when conventional peak picking introduces false positives.
    0 installs
53. ▌
    Mass Spectrometry Feature Extraction From Cardinal Objec 2 · holobiomicslab

    Use when you have a Cardinal MSImagingExperiment object (e.g., from imzML or Analyze 7.5 files) and need to retrieve the complete set of m/z values and their intensities for annotation against metabolite databases (HMDB, Lipidmaps) or for statistical analysis.
    2 installs
54. ▌
    Metabolite Cluster Identification From Correlated Featur 2 · holobiomicslab

    Use when after preprocessing, imputation, and batch correction of LC-MS peak tables when you need to group redundant or related feature measurements (e.g., [M+H]+ and [M+Na]+ adducts, or isotope peaks) into metabolite-level clusters before statistical testing or identification.
    1 install
55. ▌
    Software Performance Characterization And Scaling Analys 2 · holobiomicslab

    Use when when a tool claims to be 'scalable' or 'performance-conscious' but lacks published performance benchmarks, or when you need to confirm that runtime and memory scale linearly (or predictably) with sample count before deploying the tool on large LC-MS datasets (e.g., >100 samples).
    0 installs
56. ▌
    Mass Spectrometry Peak Identification And Extraction 2 · holobiomicslab

    Use when when you have raw mass spectrometry data from direct-infusion (DI-MS) or ambient surface analysis probe (ASAP-MS) instruments and need to identify which m/z peaks are biologically or chemically informative for sample classification, rather than processing the entire spectrum including.
    2 installs
57. ▌
    Baseline And Noise Level Estimation From Quartile Statis 2 · holobiomicslab

    Use when before peak detection on a composite or individual mass track when you need to filter out low-intensity noise and baseline drift without removing true signal.
    0 installs
58. ▌
    Cheminformatics Substructure Matching And Reaction Templ 2 · holobiomicslab

    Use when you have a chemical substrate and need to predict its biotransformation products using rule-based metabolism prediction. This applies when: (1) you possess a library of biotransformation rules extracted from a curated database (e.
    0 installs
59. ▌
    Deep Learning Model Implementation In Pytorch Or Tensorf 2 · holobiomicslab

    Use when when you need to construct a dual-branch neural network encoder that processes two augmented versions of the same input (e.g., ion images in COL or ISO mode) and must enforce weight sharing between branches to reduce parameters while maintaining separate output representations.
    0 installs
60. ▌
    Resnet Architecture Modification For Dimensionality Cont 2 · holobiomicslab

    Use when your task requires a pretrained convolutional encoder (ResNet18) to produce fixed-size representation vectors of a specific dimensionality (e.g., 512 dimensions) rather than the default output size.
    2 installs
61. ▌
    Mass Track Clustering 2 · holobiomicslab

    Use when after constructing initial data bins from mzTree (indexed by int(mz × 1000)), determine whether a single bin contains one or multiple mass tracks. Apply clustering when the m/z range of points in a bin exceeds 2 × ppm tolerance (e.
    0 installs
62. ▌
    Peak Shape Assessment 2 · holobiomicslab

    Use when after peak detection in a nontargeted LC-MS workflow when you have a feature table with detected peaks and need to filter low-quality features or understand why certain features have inconsistent intensity or poor annotation confidence.
    0 installs
63. ▌
    Spectrum Data Loading 2 · holobiomicslab

    Use when when you have a USI (e.g., mzspec:MTBLS1124:QC07.mzML) pointing to a public mzML or related spectrum file in MetaboLights, MassIVE, or GNPS repositories, and need to load the spectrum data for interactive visualization, quality control assessment, or downstream analysis.
    0 installs
64. ▌
    Xic Marker Annotation 2 · holobiomicslab

    Use when when you have a resolved spectrum file (mzML, mzXML) and need to visualize where MS2 precursor scans occur on an XIC display.
    0 installs
65. ▌
    JSON Schema Validation 2 · holobiomicslab

    Use when after extracting tabular data into intermediate JSON representation (via tagging), or after manual JSON editing, and before converting to a target format (e.g., mwTab for Metabolomics Workbench).
    2 installs
66. ▌
    File Format Validation 2 · holobiomicslab

    Use when after writing parsed spectra to a new MSP file using mssearchr's MSP writer, or when integrating MSP files from external sources into an R analysis pipeline.
    0 installs
67. ▌
    Mzml Format Validation 2 · holobiomicslab

    Use when after downloading an mzML file from a remote repository (e.g., MetaboLights, MassIVE, GNPS) via USI resolution, before attempting to parse it into a spectrum container or visualization dashboard.
    0 installs
68. ▌
    Peak M Z Recalibration 2 · holobiomicslab

    Use when after peak detection when you have a table of detected peaks with m/z values and need to improve mass accuracy for downstream annotation.
    0 installs
69. ▌
    Build System Monitoring 2 · holobiomicslab

    Use when when you need to capture a snapshot of a research software project's health metrics from multiple CI/CD and repository services (Travis CI, Landscape.
    2 installs
70. ▌
    Ccs Bias Quantification 2 · holobiomicslab

    Use when you have IM-MS lipidomics data acquired on samples spiked with fully labeled U13C lipid standards (e.g., U13C yeast extract), and you need to assess whether systematic CCS deviation exists between your instrument's measured values and the DT CCS N2 reference library for U13C labeled lipids.
    2 installs
71. ▌
    Data Summary Statistics 2 · holobiomicslab

    Use when you have a curated relational dataset (structure-organism pairs) and need to quantify how structures distribute across a categorical variable (e.g., organism prevalence).
    0 installs
72. ▌
    Lcms Feature Extraction 2 · holobiomicslab

    Use when when you have raw LC-MS chromatographic data (mzML or vendor format) and need to identify and characterize all detectable peaks across the full retention time range for untargeted metabolomics or discovery workflows.
    0 installs
73. ▌
    Lipid Class Enumeration 2 · holobiomicslab

    Use when you have a lipid identification or library-generation task that requires you to define a target chemical space bounded by lipid classes (e.g., phosphatidylcholine, triglyceride) and fatty acid composition ranges (e.g., C14–C22 with 0–6 degrees of unsaturation).
    2 installs
74. ▌
    M Z Rt Feature Matching 2 · holobiomicslab

    Use when you have extracted peaks from multiple LC/HRMS batches (n > 1) with their m/z and RT values, and you need to identify and align peaks representing the same compound across batches to build a consensus feature matrix.
    0 installs
75. ▌
    Massql Query Generation 2 · holobiomicslab

    Use when you have trained a shallow decision tree on ChemEcho feature vectors (representing unique peak or neutral loss formulas from tandem MS spectra) and need to deploy the learned splitting logic as a queryable, inspectable artifact.
    0 installs
76. ▌
    Metabolite Set Analysis 2 · holobiomicslab

    Use when you have a metabolite intensity matrix (rows=metabolites or peaks, columns=samples) paired with metabolite-to-pathway or metabolite-to-feature-group annotations, and you want to score activity levels across pathways or metabolite groupings in a way that tolerates missing peaks and.
    0 installs
77. ▌
    Mse Reconstruction Loss 2 · holobiomicslab

    Use when training embeddings from multi-modal spectral data (peak information + metadata) where you need to ensure both contrastive discriminability AND reconstruction fidelity. Specifically use it in transformer-based architectures that produce embeddings from heterogeneous inputs (e.
    0 installs
78. ▌
    Spectral Data Retrieval 2 · holobiomicslab

    Use when you have a USI string (e.g., mzspec:GNPS:TASK-d93bdbb5cdda40e48975e6e18a45c3ce-f.mwang87/data/... or mzspec:MSV000084951:AH22) and need to extract the corresponding mass spectrum peak list (m/z and intensity pairs) for downstream analysis, visualization, or cross-repository comparison.
    2 installs
79. ▌
    Spectral Token Design 2 · holobiomicslab

    Use when when you need to prepare mass spectra and molecular structures for joint modeling in a BART or transformer-based sequence model, and you lack a unified representation scheme that allows both modalities to be encoded and decoded without collision or information loss.
    0 installs
80. ▌
    Python Environment Setup 2 · holobiomicslab

    Use when you have cloned a scientific repository containing Python code (scripts, Jupyter notebooks, or module imports) and need to execute it locally or on new hardware.
    2 installs
81. ▌
    Badge Endpoint Retrieval 2 · holobiomicslab

    Use when when you need to verify the current operational status of a software project across multiple dimensions (CI/CD, code quality, test coverage, containerization, archival) and those status indicators are exposed as badge endpoints in the project's README.
    0 installs
82. ▌
    Gnps Mgf Format Handling 2 · holobiomicslab

    Use when you have mass spectrometry MS/MS spectral data in GNPS-style MGF format and need to feed it into the Mass2SMILES deep learning model for structure and functional group prediction.
    2 installs
83. ▌
    Gnps Repository Querying 2 · holobiomicslab

    Use when when you have a USI string (e.g., mzspec:GNPS:TASK-d93bdbb5cdda40e48975e6e18a45c3ce-...
    2 installs
84. ▌
    Lcms Data Format Parsing 2 · holobiomicslab

    Use when when you have raw LC/MS data in mzML format and need to execute the LAGF non-targeted screening pipeline. Use this skill as the first step before applying the LAGF algorithm workflow to extract and annotate features from mass spectrometry data.
    0 installs
85. ▌
    Ms2 Precursor Extraction 2 · holobiomicslab

    Use when when you have a resolved spectrum file in mzML or mzXML format and need to identify where MS2 (tandem mass spectrometry) scans occur within an LC-MS run, particularly to annotate XIC displays with MS2 precursor positions or validate that MS2 events align with expected chromatographic.
    0 installs
86. ▌
    Peak Formula Enumeration 2 · holobiomicslab

    Use when when you have tandem mass spectra (mz/intensity pairs with precursor m/z) and need to train interpretable machine learning models—particularly decision trees or regression models—where each feature must correspond to a concrete chemical entity (peak or neutral loss) rather than a latent.
    0 installs
87. ▌
    Peak Table Harmonization 2 · holobiomicslab

    Use when when you have extracted peak tables from multiple independent LC/HRMS analysis batches (each with retention time and m/z values) and need to align peaks across batches to create a unified feature matrix for downstream statistical analysis.
    0 installs
88. ▌
    Spectral Noise Filtering 2 · holobiomicslab

    Use when immediately after extracting ion chromatograms (EICs) by binning mass spectral data across the full m/z range from raw LC/HRMS files (mzML, mzXML, or netCDF format).
    0 installs
89. ▌
    Imzml Metadata Parsing 2 · holobiomicslab

    Use when you have received paired .imzML (XML metadata) and .ibd (binary data) files from an Imaging Mass Spectrometry instrument and need to discover the imaging geometry, m/z calibration, and scan coordinate system before extracting mass images or computing total ion chromatograms (TIC).
    0 installs
90. ▌
    Retention Time Prediction 2 · holobiomicslab

    Use when you have a set of small-molecule structures (SMILES, InChI, or SDF format) and need to predict their chromatographic retention times for a specific method, either to support metabolite annotation, validate experimental assignments, or project RTs across different chromatographic platforms.
    0 installs
91. ▌
    Candidate Formula Ranking 2 · holobiomicslab

    Use when you have an observed m/z value from mass spectrometry imaging and need to assign a chemical formula with high confidence.
    2 installs
92. ▌
    Chemical Shift Annotation 2 · holobiomicslab

    Use when when you have preprocessed 1H NMR spectral data with unidentified peaks and need to determine metabolite identity by exploiting the correlation structure of NMR signals.
    0 installs
93. ▌
    File Integrity Validation 2 · holobiomicslab

    Use when you have a raw NV (NMRViewJ) binary file and need to confirm it is well-formed before parsing or processing.
    0 installs
94. ▌
    Infoence Loss Composition 2 · holobiomicslab

    Use when when training embeddings from MS/MS spectra data where you need both discriminative power (to distinguish similar spectra) and reconstruction accuracy (to preserve peak and metadata information).
    0 installs
95. ▌
    Input Type Classification 2 · holobiomicslab

    Use when a web application receives mass spectrometry data through heterogeneous identifier formats and must automatically determine which loader (Task ID, USI, or FBMN) should process the input.
    0 installs
96. ▌
    Khipu Grid Offset Mapping 2 · holobiomicslab

    Use when you have a set of ions detected in LC-MS data that are suspected to derive from the same neutral compound via different isotope and adduct patterns. Use this skill after ions have been matched to isotope and adduct patterns and assigned to grid positions (isotope row and adduct column).
    2 installs
97. ▌
    Metabolic Network Mapping 2 · holobiomicslab

    Use when you have an untargeted metabolomics feature table (with m/z, retention time, and statistical significance values) and want to predict which metabolic pathways and functional modules are active in your sample, but you lack confident metabolite identifications or wish to bypass the.
    0 installs
98. ▌
    Mrm Transition Extraction 2 · holobiomicslab

    Use when you have raw LC-MS/MS data in MRM acquisition mode and need to systematically identify and catalog all precursor m/z and corresponding product m/z values for each transition monitored during data collection.
    2 installs
99. ▌
    Organism Taxonomy Mapping 2 · holobiomicslab

    Use when you have a cleaned organism table (with validated, deduplicated organism names from sources like NCBI, manual curation, or previous cleaning steps) and need to annotate each organism with Open Tree of Life identifiers, taxonomic lineage, and standardized taxonomic annotations.
    2 installs
100. ▌
     Otl Identifier Assignment 2 · holobiomicslab

     Use when after organism name cleaning and taxonomy verification (4_cleaningTaxonomy.R) have been completed and you have a cleaned organism table with standardized names.
     0 installs