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HolobiomicsLab

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1. ▌
   Gnps Workflow Result Processing 2 · holobiomicslab

   Use when when you have run a spectral networking job on GNPS (e.g. ProteoSAFe-METABOLOMICS-SNETS-V2) and need to reuse the network output files locally with MetaMiner or another tool that accepts spectral network input directories.
   0 installs
2. ▌
   Molecular Network Graph Parsing 2 · holobiomicslab

   Use when after GNPS_GC molecular networking job completion, when you have retrieved raw network output files and need to extract, validate, and structure the network topology for further metabolite assignment, comparative network analysis, or visualization.
   0 installs
3. ▌
   Ms2 Peak Detection And Counting 2 · holobiomicslab

   Use when you have raw MS2 spectral data (MGF, mzML, or msp format) and need to generate a sample-level fingerprint for comparison across metabolomics samples, especially when samples were acquired using different LC methods, mass spectrometer technologies, or exhibit poor feature overlap or large.
   0 installs
4. ▌
   Ms2 Spectra Parsing And Loading 2 · holobiomicslab

   Use when when beginning a MEMO analysis workflow with raw or unaligned MS2 spectra files and needing to extract fragmentation data and precursor information before counting MS2 peaks and neutral losses to generate sample fingerprints.
   0 installs
5. ▌
   Ms2lda Motif To Network Mapping 2 · holobiomicslab

   Use when when you have a GNPS molecular network (classical or feature-based) and corresponding MS2LDA experiment results, and you want to annotate network nodes with discovered substructural motifs to support structural elucidation and chemical family interpretation.
   0 installs
6. ▌
   Nearest Neighbor Index Querying 2 · holobiomicslab

   Use when you have millions of MS/MS spectra to cluster and have already constructed nearest neighbor indexes (partitioned Voronoi diagrams of spectrum vectors bucketed by precursor m/z).
   0 installs
7. ▌
   Object State Mutation Detection 2 · holobiomicslab

   Use when when calling filter functions (e.g., filter_mispicked_ions(), filter_group(), filter_cv()) on R6-based metabolomics data objects in the mpactr package and you need to verify whether the original object's state is preserved.
   0 installs
8. ▌
   Peakmap Heatmap Rendering Mz Rt 2 · holobiomicslab

   Use when when you have mass spectrometry data organized in a Pandas DataFrame with m/z values, retention time (RT), and intensity measurements, and you want to visualize the joint distribution and correlation of these three dimensions to identify peaks, assess separation, and detect patterns across.
   0 installs
9. ▌
   Raw Chromatography Data Parsing 3 · holobiomicslab

   Use when you have raw GC-MS output files (vendor formats or netCDF) from a chromatography instrument and need to prepare them for automated peak deconvolution and spectral analysis.
   0 installs
10. ▌
    Restful API Endpoint Invocation 2 · holobiomicslab

    Use when you have NMR peak data (1H and 13C chemical shift values) and need to obtain SMART 3 classification predictions from the DeepSAT service.
    0 installs
11. ▌
    Spectral Similarity Computation 2 · holobiomicslab

    Use when after inferring Mass2Motif definitions from LDA modeling when you need to build a network representation of motif relationships.
    0 installs
12. ▌
    Tandem Mass Spectrum Clustering 2 · holobiomicslab

    Use when you have a large collection of tandem mass spectra (mzML, mzXML, or MGF format) and want to group similar spectra into clusters to identify redundancy, discover novel peptides or metabolites, or prepare data for downstream annotation.
    0 installs
13. ▌
    Adduct Mass Difference Matching 2 · holobiomicslab

    Use when you have computed a histogram of pairwise mass differences from MS imaging data and need to (1) identify which observed mass differences correspond to biologically relevant or chemically known adducts, or (2) rank the most frequently observed mass differences to discover dominant adduct.
    0 installs
14. ▌
    Background Ion Blank Comparison 2 · holobiomicslab

    Use when after generating an initial LC-MS feature table (from Asari or similar peak detection) and before normalization or statistical analysis, especially when blank samples (e.g., solvent-only or buffer-only runs) were acquired alongside study samples.
    0 installs
15. ▌
    Biclustering For Omics Features 2 · holobiomicslab

    Use when you have a normalized matrix of feature attribution scores (microbes × metabolites) derived from a trained neural network, and you want to partition both microbes and metabolites simultaneously into co-clusters that share similar interaction patterns.
    0 installs
16. ▌
    Ce Ms Eof Marker Identification 2 · holobiomicslab

    Use when when processing CE-MS test files and you need to identify and extract the migration time of the EOF marker (e.g., Paracetamol) to normalize compound migration times across runs.
    0 installs
17. ▌
    Chemical Annotation Integration 2 · holobiomicslab

    Use when after training a tandem mass spectrometry embedding model (such as MSBERT) on a reference spectral library (e.g., GNPS), apply this skill to confirm that the high-dimensional embedding vectors project into interpretable chemical space.
    0 installs
18. ▌
    Chemical Identifier Unification 2 · holobiomicslab

    Use when when you have raw GC-MS output (CSV with columns: Component.RT, Base.Peak.MZ, Component.Area, Compound.Name, Match.Factor, File.
    0 installs
19. ▌
    Chromatogram Netcdf File Import 2 · holobiomicslab

    Use when you have raw GCxGC-MS chromatogram data in NetCDF (CDF) format from an instrument and need to load it into R for preprocessing (smoothing, baseline correction, peak alignment) and multivariate analysis.
    0 installs
20. ▌
    Chromatographic Peak Resolution 2 · holobiomicslab

    Use when when you have loaded raw GC-MS data in netCDF or mzML format and visual or statistical inspection reveals overlapping chromatographic peaks (i.e., multiple m/z ions co-eluting at the same retention time window).
    0 installs
21. ▌
    Classifier Prediction Inference 2 · holobiomicslab

    Use when you have a CSV or Excel file containing chemical structure descriptors for one or more molecules, and you want to obtain binary bitter/not-bitter predictions for each molecule using the BitterPredict classifier.
    0 installs
22. ▌
    Cnn Spectral Feature Extraction 2 · holobiomicslab

    Use when you have preprocessed 1D NMR spectra (¹H and/or ¹³C) and need to extract spectral features for molecular structure inference on molecules with up to 19 heavy atoms. The skill is necessary as the first stage before fragment assembly or connectivity prediction;
    0 installs
23. ▌
    Cross Language Interface Design 2 · holobiomicslab

    Use when when you have domain-specific functionality (e.g., spectral similarity scoring, peak detection algorithms) implemented in one language (Python) but need to make it callable and composable within an R-based analytical pipeline (Spectra objects);
    0 installs
24. ▌
    Cross Software Feature Matching 3 · holobiomicslab

    Use when you have collected feature lists in CSV format from two or more MS acquisition methods (e.g., LC-MS vs. LC-IMS-MS), processing software packages (e.g., vendor-specific vs. open-source), or instrument platforms (e.
    0 installs
25. ▌
    Deconvolved Spectrum Comparison 2 · holobiomicslab

    Use when after auto-deconvolution of GC-MS data has produced a table of deconvolved mass spectra, and you need to organize these spectra into clusters or detect which compounds co-elute or share similar fragmentation patterns.
    0 installs
26. ▌
    Dysregulation Score Computation 3 · holobiomicslab

    Use when you have per-sample metabolite abundance data (e.g., from LC-MS or GC-MS) and a metabolite-to-pathway assignment table, and need to generate a sample-by-pathway dysregulation matrix for downstream classification, prognosis prediction, or pathway-level phenotype association.
    0 installs
27. ▌
    Exact Mass Accuracy Calculation 2 · holobiomicslab

    Use when you have feature pairs identified by temporal correlation in direct-injection MS data and need to confirm their relationship is consistent with known adduct/fragment mass shifts.
    0 installs
28. ▌
    Feature Abundance Normalization 2 · holobiomicslab

    Use when after peak picking (e.g., via MS-DIAL) and quality control filtering, when you have a raw feature abundance matrix with intensity values across multiple samples and need to make intensities comparable before statistical testing or multivariate analysis.
    0 installs
29. ▌
    Feature Annotation Augmentation 2 · holobiomicslab

    Use when when a traditional peak extraction pipeline (e.g., XCMS) has generated a feature table from LC-MS data but fails to detect known or suspected compounds present in your sample. Specifically, when you have a suspect database (e.
    0 installs
30. ▌
    Fragment Match Rate Computation 2 · holobiomicslab

    Use when after denoising MS/MS spectra at multiple frequency thresholds and matching each thresholded spectrum against a -matching reference spectrum.
    0 installs
31. ▌
    Functional Group Classification 2 · holobiomicslab

    Use when you have a set of query chemicals (chemical names or structures) and need to match them against a reference chemical library organized by type or category, with the goal of identifying structural similarity, functional group membership, or categorical assignment.
    0 installs
32. ▌
    Gcf Mf Hierarchical Aggregation 2 · holobiomicslab

    Use when when you have predicted BGC-spectrum IOKR scores or other pairwise linking scores, and need to rank genomic clusters (GCFs from BiG-SCAPE) against metabolomic clusters (MFs from MS/MS spectra grouping), particularly in NPLinker workflows where one GCF may contain multiple BGCs and one MF.
    0 installs
33. ▌
    Gcf Mf Link Scoring Computation 2 · holobiomicslab

    Use when you have paired GCF and MF datasets with strain membership information and need to rank candidate GCF–MF links to identify which biosynthetic gene clusters likely produce detected metabolites.
    1 install
34. ▌
    Gradient Based Saliency Mapping 2 · holobiomicslab

    Use when you have a trained graph neural network model for CCS prediction and need to identify which molecular structural features drive individual predictions or systematic biases.
    0 installs
35. ▌
    Igzip Header Structure Encoding 2 · holobiomicslab

    Use when when implementing an igzip parser, decoder, or validator that must interpret the custom header format; when debugging igzip file corruption or encoding errors; or when extending pymzML's igzip support to handle new index schemes.
    0 installs
36. ▌
    Interactive Workflow Validation 2 · holobiomicslab

    Use when after automated peak detection has identified candidate peaks from LC-MS mzML files, but before exporting the final metabolite library. Use this skill when you need to: (1) optimize noise and peak-detection parameters by visualizing their effect on a representative subset of peaks;
    0 installs
37. ▌
    Ion Mobility Reference Matching 2 · holobiomicslab

    Use when you have raw arrival-time data from TWIM-MS and need to convert it to collision cross section (CCS) values for multi-omic analysis.
    0 installs
38. ▌
    Isotope Mass Offset Enumeration 3 · holobiomicslab

    Use when you have a detected feature table (m/z, drift_time, retention_time, intensity) from LC-IMS-MS or similar multidimensional MS data and want to identify and annotate isotopic families (e.g., singly-charged C13 patterns).
    0 installs
39. ▌
    Jms Compliant Database Querying 2 · holobiomicslab

    Use when you have grouped LC-MS features into empirical compounds with inferred molecular formulas and adduct assignments (via khipu), and you need to assign candidate metabolite identities at Level 4 annotation depth by matching against curated reference libraries.
    0 installs
40. ▌
    JSON Schema Output Verification 2 · holobiomicslab

    Use when after extracting tabular data into intermediate JSON form or after applying matrix conversion directives (e.
    0 installs
41. ▌
    Lc Ms Data Structure Validation 2 · holobiomicslab

    Use when before launching TARDIS peak detection on a new LC–MS dataset or target compound list. Apply this skill when you have raw MS data files in vendor formats (e.g., .raw, .d) and/or a spreadsheet-based target list (.xlsx or .
    0 installs
42. ▌
    Lc Ms Profile Data Segmentation 2 · holobiomicslab

    Use when you have raw profile (not centroided) LC-MS data in .mzML format and need to prepare it for automated peak detection using a trained object detection network.
    0 installs
43. ▌
    Lcms Feature Table Construction 2 · holobiomicslab

    Use when you have centroided, single-polarity mzML files from DDA LC-MS experiments and need to generate a quantitative feature table with aligned m/z and retention time coordinates, isotopic annotations, and MS2 spectra for downstream statistical or annotation analysis.
    0 installs
44. ▌
    Lda Result Database Persistence 2 · holobiomicslab

    Use when after running gensim LDA on a corpus of MS2 fragmentation features, when you need to store the LDA results (topics, document-topic assignments, term-topic distributions) in a PostgreSQL database so they can be queried and visualized by a Django web application or other downstream consumers.
    0 installs
45. ▌
    Lipid Ontology Category Mapping 2 · holobiomicslab

    Use when you have a list of detected lipids (e.g., from LC-MS/MS lipidomics data) with associated statistical measures (p-values, fold-changes), and you need to test whether specific lipid ontology categories (e.
    0 installs
46. ▌
    Lipid Type Category Enumeration 2 · holobiomicslab

    Use when when you have downloaded or cloned a lipidomics library repository (such as LipidMatch) and need to audit the breadth of lipid-type coverage to ensure the library meets minimum requirements for your analysis scope (e.g., ≥60 distinct lipid categories).
    0 installs
47. ▌
    Machine Learning Model Training 3 · holobiomicslab

    Use when you have a labeled dataset of DIA raw files (.raw, .d, .wiff) with known quality annotations and have extracted the 15 iDIA-QC metrics (raw file characteristics from timsTOF, TripleTOF, or Orbitrap instruments).
    0 installs
48. ▌
    Mass Action Law Flux Prediction 2 · holobiomicslab

    Use when when you have quantified intracellular metabolite abundances (LC-MS normalized values) from multiple samples and need to predict how differences in substrate availability translate into differences in metabolic flux for specific reactions in a constraint-based metabolic model.
    0 installs
49. ▌
    Mass Spectral Matrix Prediction 2 · holobiomicslab

    Use when you have raw GC-MS data with overlapped peaks in a specific retention time region and need to resolve the individual pure mass spectra of all components present in that region.
    0 installs
50. ▌
    Mass Spectrometry Data Querying 2 · holobiomicslab

    Use when you have a directory of mzML mass spectrometry files and need to systematically identify and extract scans or peaks matching specific m/z values, retention time windows, intensity thresholds, or spectral fingerprints (e.g., product ion patterns, neutral loss signatures).
    0 installs
51. ▌
    Mass2motif Network Construction 2 · holobiomicslab

    Use when after MS2LDA has inferred a motifset and you need to visualize and export the relationships between discovered Mass2Motifs for post-processing exploration, comparative annotation, or integration with external tools. Use this skill when you have motifset.json or motifset_optimized.
    0 installs
52. ▌
    Mass2motif Substructure Mapping 2 · holobiomicslab

    Use when you have created a GNPS molecular network (classical or feature-based workflow) and run an MS2LDA experiment on the corresponding MGF spectra, and you want to annotate network nodes with shared Mass2Motifs and chemical class information to interpret the structural basis of network.
    0 installs
53. ▌
    Metabolite Metadata Integration 2 · holobiomicslab

    Use when when you have separate quantification data (abundance matrix), sample metadata (phenotypes, treatment groups, experimental conditions), and spectral data (MS/MS fragmentation patterns or other spectral features) that must be combined for mass spectrometry-based metabolite analysis.
    0 installs
54. ▌
    Metabolite Set Activity Scoring 3 · holobiomicslab

    Use when when you have log2-normalized, standardized peak intensity data (rows=peaks, columns=samples) with compound annotations (peak-to-metabolite mappings via KEGG/ChEBI IDs) and need to collapse individual peak signals into pathway-level summary scores for statistical comparison across.
    0 installs
55. ▌
    Molecular Geometry File Parsing 2 · holobiomicslab

    Use when when you have a molecular structure in XYZ or similar coordinate format and need to initialize QCxMS2 or related workflows for EI mass spectrum calculation.
    0 installs
56. ▌
    Ms Annotation Result Validation 2 · holobiomicslab

    Use when after running annotateRC on LC–MS AIF features with fragment libraries (e.
    0 installs
57. ▌
    Ms2 Spectral Feature Extraction 2 · holobiomicslab

    Use when you have LC-MS/MS metabolomics data in MGF format and need to prepare it for Latent Dirichlet Allocation (LDA) topic modeling.
    0 installs
58. ▌
    Ms2 Spectral Similarity Scoring 2 · holobiomicslab

    Use when after temporal intensity profile correlation and exact mass difference refinement have identified candidate ion-species pairs in direct-injection plasma ionization MS data (e.g., DBDI-MS, DBDI-FT-ICR-MS).
    0 installs
59. ▌
    Multi Dimensional Data Encoding 2 · holobiomicslab

    Use when you have loaded LC-MS feature tables or peak detection output containing internal standard identifications with retention times, m/z values, and intensity measurements across multiple samples, and you need to detect anomalies such as retention time drift, m/z shifts, or intensity loss that.
    0 installs
60. ▌
    Multi Key Sorting And Filtering 2 · holobiomicslab

    Use when when converting tabular data to JSON via the matrix directive, you need to exclude records that fail domain-specific validation (e.g., only retain records where a 'test' condition evaluates to true) and/or reorder the output list by one or more fields in ascending or descending order.
    0 installs
61. ▌
    Multi Source Spectrum Retrieval 2 · holobiomicslab

    Use when when you have a Universal Spectrum Identifier (USI) string or collection of USI strings and need to programmatically retrieve the corresponding mass spectrometry spectrum data from one of seven supported repositories (GNPS Molecular Networking, GNPS Spectral Libraries, ProteoXchange.
    0 installs
62. ▌
    Mzml File Parsing And Ingestion 2 · holobiomicslab

    Use when you have raw profile LC-MS data in .mzML format and need to prepare it for targeted or untargeted peak detection.
    0 installs
63. ▌
    Neutral Mass Derivation From Mz 2 · holobiomicslab

    Use when after adduct configuration is complete and before querying formula databases. Use it whenever you have m/z peak lists from mass spectrometry data and need to identify the neutral mass underlying each observed ion, particularly when multiple adduct types are active in the same experiment.
    0 installs
64. ▌
    Nextflow Pipeline Orchestration 2 · holobiomicslab

    Use when when you have raw LC-HRMS metabolomics data in .mzML or .
    0 installs
65. ▌
    Nmr Workflow Pipeline Execution 2 · holobiomicslab

    Use when you have raw 1D NMR spectra (FID or processed spectrum files) and need to extract peak parameters (chemical shift, intensity, linewidth) in a tabular format for downstream metabolomic or structural analysis.
    0 installs
66. ▌
    Notification Payload Formatting 2 · holobiomicslab

    Use when when a QC check fails during an LC-MS instrument run and you need to alert users in real time.
    0 installs
67. ▌
    Object Detection Model Training 2 · holobiomicslab

    Use when you have annotated LC-MS ROI snippets with ground-truth peak/non-peak labels and boundary coordinates (peak start/end positions), and you need to build a model that can discriminate true peaks from false peaks while precisely localizing peak boundaries for area integration in future LC-MS.
    0 installs
68. ▌
    Order Agnostic Dispatch Routing 2 · holobiomicslab

    Use when when your untargeted LC-MS pipeline must support multiple peak-picking backends and you need to let users specify which algorithm to use (via configuration file or parameter) without hard-coding algorithm dependencies.
    0 installs
69. ▌
    Package Repository Verification 2 · holobiomicslab

    Use when releasing a new version of a Python package to public repositories, when verifying that distribution pipelines are functioning after code changes, or when troubleshooting installation failures reported by users across different platforms (Linux, macOS) or architectures (x86_64, aarch64).
    0 installs
70. ▌
    Post Hoc Model Interpretability 2 · holobiomicslab

    Use when after training a GNN model on molecular structures with continuous targets (e.g., CCS values), when you need to understand which node-level (atom) or edge-level (bond) features contribute most to individual or aggregate predictions.
    0 installs
71. ▌
    Prediction Sensitivity Analysis 2 · holobiomicslab

    Use when you have a trained predictor (like BitterPredict) that accepts structured descriptors and want to understand feature importance without retraining.
    0 installs
72. ▌
    Psm Annotation And Ion Matching 2 · holobiomicslab

    Use when when you have an MS2 scan with observed peak data (m/z, intensity, charge state), a known peptide sequence, and need to determine which observed ions correspond to B and Y fragment ions. Apply this skill particularly when working with natural abundance (1.
    0 installs
73. ▌
    Python R Data Structure Mapping 2 · holobiomicslab

    Use when when you have mass spectrometry data in R's Spectra format but need to leverage Python libraries (matchms, spectrum_utils) for specialized operations like spectral similarity scoring, filtering, or normalization that lack native R implementations or perform better in Python.
    0 installs
74. ▌
    Python Sqlite Migration And Etl 2 · holobiomicslab

    Use when you have MS/MS spectral library data currently stored in multiple file formats (JSON, CSV, or binary) and need to enable fast, filtered queries by metadata (e.g., precursor m/z, retention time, molecular class) without loading entire libraries into memory.
    0 installs
75. ▌
    Ranked Candidate Prioritization 2 · holobiomicslab

    Use when you have a feature quantification table (m/z, retention time, peak areas) and candidate metabolite annotations (chemical identifiers, MS/MS spectra matches, or SIRIUS/GNPS predictions) linked to a sample organism or taxon, and you need to prioritize which candidates are most biochemically.
    0 installs
76. ▌
    REST API Contract Documentation 2 · holobiomicslab

    Use when a webservice component (like MAGMa's joblauncher) lacks formal API documentation but the source code is accessible, and downstream consumers (web applications, external services) need to understand available HTTP endpoints, parameter schemas, and response formats without manual.
    0 installs
77. ▌
    Roi Detection Mass Spectrometry 3 · holobiomicslab

    Use when you have raw or converted mass spectrometry data (CE-MS or LC-MS in mzXML or mzML format) and need to identify candidate metabolite regions before feature extraction.
    0 installs
78. ▌
    Service Health Check Definition 2 · holobiomicslab

    Use when when deploying a multi-service microarchitecture (such as MAGMa's four distinct subprojects: magmaweb, joblauncher, job, and pubchem) via Docker Compose and you need to ensure that service startup order respects true readiness rather than container existence—particularly when services have.
    0 installs
79. ▌
    Spectral Data Format Conversion 3 · holobiomicslab

    Use when you have raw tandem mass spectrometry data in one or more of the vendor formats (MGF, mzML, or msp) and need to apply unsupervised topic modeling (LDA-based motif discovery) or comparative fragmentation analysis.
    0 installs
80. ▌
    Spectral Data Format Validation 2 · holobiomicslab

    Use when after converting existing mass spectrometry formats (mzML, vendor formats) into mzPeak using command-line tools or when receiving mzPeak files from external sources.
    0 installs
81. ▌
    Spectral Data Import Validation 2 · holobiomicslab

    Use when when you have raw mass spectrometry data in one or more of the six supported file formats (mzML, mzXML, msp, metabolomics-USI, MGF, JSON) and need to transform it into matchms spectrum objects for processing, cleaning, or similarity comparisons.
    0 installs
82. ▌
    Spectral Intensity Thresholding 2 · holobiomicslab

    Use when you have loaded raw INADEQUATE NMR spectrum data and need to distinguish true molecular peaks from noise and instrumental artifacts.
    0 installs
83. ▌
    Spectral Metadata Schema Design 2 · holobiomicslab

    Use when you are implementing a file parser or data ingestion module that must read .raw (Thermo) and .mzml files from heterogeneous LC-MS instruments and pass structured data to downstream tools (e.
    0 installs
84. ▌
    Spectral Modality Preprocessing 2 · holobiomicslab

    Use when you have downloaded raw spectroscopic data files (NMR, HSQC, COSY, IR modalities) from the Zenodo repositories and need to convert them into the standardized multi-modal input format required by the MultiModalSpectralTransformer before inference or retraining.
    0 installs
85. ▌
    Spectral Peak Clustering Gc Ims 3 · holobiomicslab

    Use when after peak detection on individual GC-IMS samples, when you need to assign consistent cluster IDs to peaks detected across multiple samples to enable cross-sample comparison and quantification.
    0 installs
86. ▌
    Spectral Peak Fragment Matching 2 · holobiomicslab

    Use when you have MS/MS spectral data (mzML, mzXML format) and a parent mass or molecular formula, and you need to identify the metabolite(s) responsible for the observed fragmentation pattern by scoring candidates against their theoretical fragmentation profiles.
    0 installs
87. ▌
    Statistical Enrichment Analysis 2 · holobiomicslab

    Use when you have ranked GCF-MF (Gene Cluster Family–Molecular Family) links using two or more independent scoring functions and a set of experimentally validated links.
    0 installs
88. ▌
    Statistical Result Reproduction 2 · holobiomicslab

    Use when you have downloaded a Jupyter notebook from a published metabolomics workflow repository (e.
    0 installs
89. ▌
    Structure Similarity Comparison 2 · holobiomicslab

    Use when after executing a molecular structure prediction model on spectroscopic input data and obtaining predicted molecular structures in a standardized format (e.g., SMILES, MOL, SDF).
    0 installs
90. ▌
    Structure Similarity Evaluation 2 · holobiomicslab

    Use when after an NMR-based structure prediction model has generated predicted molecular structures (formula and connectivity) for a test set of molecules with up to 19 heavy atoms.
    0 installs
91. ▌
    Tandem Ms Output Interpretation 2 · holobiomicslab

    Use when you have received spectrum predictions (fragment masses and intensities) from a neural model (ICEBERG, SCARF, or similar) and need to extract structural information, rank candidate molecules, or validate predictions against experimental spectra.
    0 installs
92. ▌
    Tanimoto Similarity Computation 2 · holobiomicslab

    Use when you have a trained MS2DeepScore neural network and a set of MS/MS spectra (52 binned peaks per spectrum after preprocessing) for which you need to compute pairwise structural similarity predictions.
    0 installs
93. ▌
    Transformer Input Preprocessing 2 · holobiomicslab

    Use when preparing chemical formulae (e.g., 'C6H12O6') as inputs to a transformer-based neural network for MS/MS spectrum scoring. Use it specifically when the transformer must rank multiple candidate formulae against an observed mass spectrum and element composition constraints are important;
    0 installs
94. ▌
    Untargeted Lcms Peak Annotation 2 · holobiomicslab

    Use when you have a peak-intensity matrix from untargeted LC-MS analysis (raw detected peaks with m/z and intensity values) and need to assign putative metabolite identities.
    0 installs
95. ▌
    Webassembly Local Loading Setup 2 · holobiomicslab

    Use when you have downloaded a web application (e.g., COLMARvista) that uses WebWorker and WebAssembly components and need to run it locally by opening index.html in a browser, rather than accessing it through a web server.
    0 installs
96. ▌
    Workflow Branching Logic Design 2 · holobiomicslab

    Use when when a spectral matching tool produces mixed output containing both exact library matches and analog search results, and your analysis or publication requires separate handling, interpretation, or reporting of these two match classes.
    0 installs
97. ▌
    Xcms Parameter Optimization Msw 3 · holobiomicslab

    Use when when you have direct-injection or low-complexity mass spectrometry data (mzML files) and need to detect chromatographic peaks using wavelet-based methods instead of centWave, especially when standard retention-time-dependent peak detection is not suitable or when you need to tune.
    0 installs
98. ▌
    Ccs Prediction Model Design 2 · holobiomicslab

    Use when you have a dataset of molecules with known or reference CCS values, and you need to construct a trainable model that learns the mapping from molecular structure (encoded as SMILES or feature vectors) to scalar CCS predictions.
    0 installs
99. ▌
    Im Ms Drift Time Correction 3 · holobiomicslab

    Use when when you have IM-MS lipidomics data acquired on samples spiked with U13C-labeled internal standards (fully labeled yeast extract) and need to quantify systematic CCS bias and apply lipid class-specific bias correction to all measured CCS values, particularly when multiple lipids per lipid.
    0 installs
100. ▌
     Multi Omic Data Integration 2 · holobiomicslab

     Use when you have raw or processed TWIM-MS data with arrival time and m/z dimensions, and you need to assign biomolecular class labels and compute class-specific CCS values across multiple compound classes simultaneously, particularly when you lack pre-identified feature peaks or want to bypass.
     0 installs