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HolobiomicsLab

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1. ▌
   Spectrum Preprocessing Precursor Masking · holobiomicslab

   Use when when training a formula-prediction model with a frozen pretrained TCN spectrum encoder and unfrozen FormulaEncoder and RescoreHead components, or when you suspect the model may use precursor intensity as a spurious feature rather than fragment-pattern information for molecular formula.
   0 installs
2. ▌
   Tandem Mass Spectra Embedding Generation · holobiomicslab

   Use when you have tandem mass spectra (in .msp or compatible format) from instruments like Orbitrap, and you need to compute library matching scores, cluster spectra by chemical similarity, or embed spectra into a learned vector space for downstream similarity or clustering tasks.
   0 installs
3. ▌
   Technical Variation Removal In Lcms Data · holobiomicslab

   Use when after merging feature tables from non-targeted LC-MS/MS data and before statistical analysis, when samples were acquired across multiple instrument runs, different days, or instrumental calibration cycles.
   0 installs
4. ▌
   Theoretical Isotope Envelope Calculation · holobiomicslab

   Use when when processing mass spectrometry data from stable isotope probing (SIP) experiments where peptides contain known levels of heavy isotope incorporation (13C, 15N, 2H, 18O), and you need to annotate observed MS2 peaks by matching them to theoretical B and Y ion fragments.
   0 installs
5. ▌
   Time And Memory Complexity Visualization · holobiomicslab

   Use when when deploying a metabolomics processing tool (such as asari) and needing to predict resource requirements or validate claimed scalability on laptop-class hardware (≤16 GB RAM, single CPU core).
   2 installs
6. ▌
   Unknown Chemical Extraction From Spectra · holobiomicslab

   Use when when you have an existing real mzML file from a metabolomics LC-MS/MS acquisition (e.g., beer or urine samples) and need to populate a virtual mass spectrometer with the actual chemicals that were measured, so that you can replay the acquisition with alternative fragmentation strategies (e.
   0 installs
7. ▌
   Untargeted Metabolomics Feature Analysis · holobiomicslab

   Use when you have a feature table from untargeted metabolomics (with m/z, retention time, and p-values from differential abundance testing) but lack or wish to bypass metabolite annotation.
   2 installs
8. ▌
   Compound Identification Ranking Evaluation · holobiomicslab

   Use when after training a FlavorFormer model end-to-end with weighted loss on 1H NMR spectra and compound labels, apply this skill to a held-out test set to measure compound identification accuracy and ranking quality.
   0 installs
9. ▌
   Fragment Assembly Transformer Architecture · holobiomicslab

   Use when when you have 1D NMR spectra (1H and/or 13C) of an unknown compound with up to ~19 heavy atoms and need to predict both molecular formula and connectivity without manual structure hypothesis generation.
   0 installs
10. ▌
    Linear Score Calculation From Coefficients · holobiomicslab

    Use when when you have 1H-NMR metabolite measurements from Nightingale Health assayed on a new cohort and wish to compute risk scores (e.g., all-cause mortality, cardiovascular event, type 2 diabetes) using published metabolic biomarker weights from a reference study.
    0 installs
11. ▌
    Metabolic Age Prediction From Nmr Features · holobiomicslab

    Use when you have Nightingale Health 1H-NMR metabolomics data (feature matrix with named metabolite columns) and need to compute predicted metabolic age for each sample, typically to assess whether individuals' metabolic profiles align with or diverge from age-expected trajectories.
    2 installs
12. ▌
    Metabolomics Model Coefficient Application · holobiomicslab

    Use when you have a matrix of Nightingale Health 1H-NMR metabolomics measurements (samples × features) and need to generate predicted metabolic scores published in peer-reviewed studies (MetaboAge, mortality score, cardiovascular event risk, Type-2 diabetes score, COVID-severity score, or surrogate.
    0 installs
13. ▌
    Multi Modal Spectroscopic Data Integration · holobiomicslab

    Use when you have acquired complementary spectroscopic measurements (NMR, HSQC, COSY, IR) for the same molecular sample and need to combine them for structure elucidation.
    0 installs
14. ▌
    Pre Analytical Delay Effect Quantification · holobiomicslab

    Use when you have uploaded a pre-analytical data table containing sample metadata, processing delay annotations (pre- and post-centrifugation timestamps or duration), and paired NMR metabolomic measurements for a sample cohort, and you need to quantify how delays at different time-points affect.
    1 install
15. ▌
    Published Metabolic Profile Implementation · holobiomicslab

    Use when you have Nightingale Health 1H-NMR metabolomics measurements for a new cohort and wish to compute one or more established metabolic risk scores (mortality, MetaboAge, cardiovascular event, type-2 diabetes, COVID-19 severity) without recalibration.
    0 installs
16. ▌
    Spectral Quality Filtering Signal To Noise · holobiomicslab

    Use when you have raw spectroscopic datasets (NMR, HSQC, COSY, IR) in standardized array or DataFrame format and need to curate them for multimodal transformer training.
    0 installs
17. ▌
    Structural Scaffold Feature Identification · holobiomicslab

    Use when you have 2D NMR spectral data (HSQC, HMBC, COSY) from multiple samples in a library or mixture and need to identify which structural scaffolds are shared across samples, prioritize samples for further analysis based on scaffold novelty or frequency, or characterize the core structural.
    0 installs
18. ▌
    Background Peak Selection Normalization · holobiomicslab

    Use when after computing expected accessibility from filtered peak and sample counts, and before computing final deviation scores. Use this skill when working with sparse ATAC-seq or DNase-seq data where GC bias and accessibility depth are known confounders of motif-associated variability.
    2 installs
19. ▌
    Benchmark Table Parsing And Aggregation · holobiomicslab

    Use when you are reproducing a comparative benchmarking claim (e.
    0 installs
20. ▌
    Chromatin Accessibility Bias Correction · holobiomicslab

    Use when you have loaded raw ATAC-seq fragment counts into a SummarizedExperiment object and are preparing to compute motif deviations.
    0 installs
21. ▌
    Numeric Range Validation Bioinformatics · holobiomicslab

    Use when after applying a quantitative analysis function (e.g., cooltools.insulation, contact frequency calculations) to Hi-C cooler files or other genomic datasets, validate that the output numeric columns contain values within plausible ranges (e.
    0 installs
22. ▌
    Pep8 Code Style Compliance Verification · holobiomicslab

    Use when developing or reviewing Python code for a scientific package (e.g., cooltools) that targets collaborative development with multiple contributors.
    0 installs
23. ▌
    Chemical Structure Similarity Matching · holobiomicslab

    Use when when you have a set of query chemicals (e.g., ethyl hexanoate, methyl salicylate) and need to find their -matched structural analogues within a reference library (e.
    0 installs
24. ▌
    Community Dependent Reaction Inference · holobiomicslab

    Use when you have consensus metabolic reconstructions for multiple community members (e.g., plant-associated microbes or plant-microbial consortia) and those individual models contain incomplete or disconnected metabolic pathways.
    0 installs
25. ▌
    Cosine Annealing Schedule Optimization · holobiomicslab

    Use when when training a regularized deep neural network for molecular property regression (e.g., retention time prediction on the METLIN SMRT dataset with 80,038+ samples), use cosine annealing warm restarts to escape plateaus and improve convergence.
    2 installs
26. ▌
    CSV Data Aggregation And Deduplication · holobiomicslab

    Use when when you have downloaded a multi-file .csv library repository (e.g., LipidMatch) and need to verify that it meets minimum thresholds for species diversity (e.g., 500,000+ distinct lipid species) and category breadth (e.g., 60+ lipid-type categories).
    1 install
27. ▌
    Custom Code Execution In Data Pipeline · holobiomicslab

    Use when when standard conversion directives (headers, collate, fields_to_headers, exclusion_headers, values_to_str, sort_by, test) cannot express the required transformation logic, or when domain-specific aggregation, conditional logic, or value derivation must be applied to records after field.
    0 installs
28. ▌
    Dimensionality Reduction Visualization · holobiomicslab

    Use when after generating large feasible flux distributions (e.g., 1 million sampled solutions per cell line) from constrained metabolic models, apply t-SNE when you need to assess whether distinct biological samples (e.
    0 installs
29. ▌
    Dynamic Method Signature Introspection · holobiomicslab

    Use when when building an automated converter discovery and job enumeration system where converter classes are dynamically loaded from package directories and you need to extract and validate their internal conversion method signatures without prior knowledge of which converters will be available.
    2 installs
30. ▌
    Execution Time Aggregation By Category · holobiomicslab

    Use when you have measured execution times from multiple scripts that exercise different combinations of categorical variables (e.g., plot types: chromatogram, mobilogram, peakmap, peakmap-marginals, spectrum, subplots;
    0 installs
31. ▌
    Feature Condition Comparative Analysis · holobiomicslab

    Use when when you have molecular structures, a regression target (e.g. retention time), and want to establish whether one class of molecular features (e.g., fingerprints) outperforms another (e.g., descriptors) or whether combining them yields marginal gains.
    0 installs
32. ▌
    Fingerprint Vector Loading And Parsing · holobiomicslab

    Use when when you have deposited or archived biosynfoni fingerprint vectors (such as from Zenodo 10.5281/zenodo.14822624) and need to ingest them into a Python workflow to compute distributional statistics, bit-frequency profiles, sparsity metrics, or pairwise similarity coefficients.
    0 installs
33. ▌
    Fragment Canonicalization And Matching · holobiomicslab

    Use when you have a collection of molecular fragments (e.g., from molecular decomposition, retrosynthesis, or synthetic planning) that must be matched to known fragment libraries or standardized representations before feeding them into a transformer assembly model.
    2 installs
34. ▌
    Inchikey Structural Similarity Scoring · holobiomicslab

    Use when you have candidate library matches from MS2Deepscore ranking (top 2000 spectra per query) with InChIKey annotations, and need to quantify structural similarity between query and candidate compounds to inform downstream match ranking and filtering by MS2Query's random forest model.
    0 installs
35. ▌
    Internal Standardization Lipid Mapping · holobiomicslab

    Use when you have (LC-)IM-MS lipidomics data from samples spiked with U13C-labeled yeast extract, measured CCS values for both labeled and unlabeled lipids, and need to quantify systematic CCS bias between your instrument and a reference library before applying bias correction.
    0 installs
36. ▌
    Mass Spectrum Histogram Interpretation · holobiomicslab

    Use when after computing all pairwise mass differences from a mass spectrometry imaging dataset, when you need to identify which mass differences correspond to real molecular adducts (e.g., metabolite–matrix or metabolite–salt ions) rather than noise.
    2 installs
37. ▌
    Metabolite Background Set Construction · holobiomicslab

    Use when when preparing to run Over-representation Analysis (ORA) on metabolomics pathway data, after you have loaded both a metabolomics pathway database (e.g., KEGG, MetExplore) and an experimental detection list (metabolites measured in your study).
    0 installs
38. ▌
    Metadata Field Extraction From Headers · holobiomicslab

    Use when you have tabular data (CSV or Excel) with column headers annotated using MESSES tagging syntax (#<table_name>.id for record identifiers, #.
    0 installs
39. ▌
    Microbe Metabolite Module Construction · holobiomicslab

    Use when when you have trained multi-layer perceptron neural network models on paired microbiome-metabolome data (from ≥10-fold cross-validation iterations) and need to identify functional modules—groups of microbes and metabolites with co-varying or synergistic relationships—for systems-level.
    0 installs
40. ▌
    Molecular Graph Representation Parsing · holobiomicslab

    Use when you have molecular identifiers (SMILES strings or molecular structure files) that need to be converted into node-edge graph tensors for input to message passing neural network models like chemprop or chemprop-IR.
    0 installs
41. ▌
    Multiple Testing Correction Bonferroni · holobiomicslab

    Use when when you have computed raw p-values for multiple independent statistical tests (e.g., Pearson correlation tests across all pairwise ion combinations in MSI data) and need to report which results remain significant after accounting for multiple comparisons.
    2 installs
42. ▌
    Package Version Compatibility Checking · holobiomicslab

    Use when after creating a fresh conda environment from a pinned dependency specification (environment.yml or requirements.txt) and installing packages via conda and/or pip.
    0 installs
43. ▌
    Python Package Dependency Installation · holobiomicslab

    Use when you need to enable optional modules in Pyteomics that depend on external libraries not bundled with the core package—such as h5py and hdf5plugin for mzMLb format access, sqlalchemy for Unimod database queries, or psims for ProForma parsing.
    0 installs
44. ▌
    Rdkit Molecular Descriptor Computation · holobiomicslab

    Use when when annotating .msp mass spectrometry files with chemical structure metadata and you need fast, offline molecular transformations (SMILES↔InChI, canonical SMILES generation) without network latency or service availability constraints;
    0 installs
45. ▌
    Robustness Analysis Under Perturbation · holobiomicslab

    Use when you have completed pathway analysis using multiple competing methods (e.g., PALS, ORA, GSEA) on a metabolomics peak intensity dataset and need to verify that ranking results remain stable when input data is intentionally corrupted.
    2 installs
46. ▌
    Search Mode Configuration Optimization · holobiomicslab

    Use when when you have a calibrated FT-ICR mass spectrum (e.g., ESI-NEG mode) and need to decide between rapid single-assignment (first_hit=True) and exhaustive multi-assignment (first_hit=False) modes.
    1 install
47. ▌
    Spectra Data Extraction And Subsetting · holobiomicslab

    Use when when you need to extract m/z and intensity peak values from a Spectra object backed by MsBackendMzR or similar on-disk backends; when analyzing subsets of spectra without loading all peaks into memory;
    0 installs
48. ▌
    Spectrum Record Consistency Validation · holobiomicslab

    Use when when you have a mass spectrometry data file (such as mzPeak) that has been read by two or more independent implementations (e.g., Rust, Python/pyarrow, R/arrow) and need to verify that all implementations produce identical spectrum metadata, data types, row counts, and numerical values.
    0 installs
49. ▌
    Statistical Distribution Visualization · holobiomicslab

    Use when after computing aggregate statistics (mean, median, standard deviation, frequency distributions, similarity coefficients) over a large dataset of molecular fingerprints or feature vectors, when you need to verify that computed metrics exhibit expected distributional shapes and to identify.
    0 installs
50. ▌
    Batch Effect Correction And Adjustment · holobiomicslab

    Use when your m/z peak data spans multiple batches (recorded in metadata as a batch ID column) or samples have varying concentrations that are documented in metadata.
    0 installs
51. ▌
    Batch Effect Correction Chromatography · holobiomicslab

    Use when when analyzing untargeted LC/HRMS data from population-scale projects (n > 500) spanning multiple sample batches or instrument runs, peaks with identical or near-identical m/z values appear at systematically shifted retention times across batches due to instrument drift, column aging, or.
    0 installs
52. ▌
    Biosynthetic Gene Cluster Tokenization · holobiomicslab

    Use when you have GenBank-formatted BGC records and need to prepare them for sub-cluster detection, domain pattern analysis, or comparison across multiple BGCs.
    2 installs
53. ▌
    Bonferroni Multiple Testing Correction · holobiomicslab

    Use when when you have performed many pairwise correlation tests between candidate parent and adduct ion intensity pairs in MSI data and need to identify statistically significant relationships while controlling for multiple-comparison bias.
    0 installs
54. ▌
    Calibration Curve Fitting Metabolomics · holobiomicslab

    Use when your experiment contains calibration-line samples with known spiked concentrations and you need to convert compound/internal-standard ratios into absolute concentrations for study samples (those with concentration = NA).
    0 installs
55. ▌
    Cascade Search Strategy Implementation · holobiomicslab

    Use when when performing open modification spectral library searches on high-resolution mass spectra where computational cost is prohibitive if every query is scored against every library spectrum.
    0 installs
56. ▌
    Chemical Similarity Metric Aggregation · holobiomicslab

    Use when when you have an unknown metabolite compound with mass spectral data, have retrieved candidate structures from a molecular structure database (PubChem, HMDB), and have obtained predictions of structurally related metabolites from a deep-learning semantic similarity model (e.g., DeepMASS2).
    0 installs
57. ▌
    Chemical Structure Format Verification · holobiomicslab

    Use when working with mass spectrometry spectral libraries (GNPS, MoNA, MTBLS1572, MassBank) that have been preprocessed by prior teams but may contain formatting errors or entries with missing/null SMILES fields.
    0 installs
58. ▌
    Chemical Structure To Taste Prediction · holobiomicslab

    Use when you have a CSV or EXCEL file containing molecular descriptors (pre-computed structural features) for one or more chemical compounds, and you need binary bitterness predictions (bitter vs. non-bitter) for each molecule.
    0 installs
59. ▌
    Chemical Transformation Library Lookup · holobiomicslab

    Use when you have a histogram of mass differences (from pairwise comparisons of detected m/z values in MALDI-MS or MSI data) and need to annotate which differences correspond to known molecular adducts—particularly when investigating unexpected or ambiguous peaks in the mass spectrum, or when.
    0 installs
60. ▌
    Colocalization Coefficient Computation · holobiomicslab

    Use when you have two co-registered LA-ICP-MS element channel images and need to quantify whether their spatial distributions are statistically correlated or independent. Use it specifically when investigating whether two elements co-occur spatially (e.
    2 installs
61. ▌
    Compound Class Prediction From Spectra · holobiomicslab

    Use when you have an unknown mass spectrometry spectrum (acquired experimentally or computationally) and need to assign it to a known drug class or identify candidate structures.
    0 installs
62. ▌
    Computational Performance Benchmarking · holobiomicslab

    Use when you have multiple candidate normalization methods for metabolomics data and need to choose one based on both statistical robustness and computational cost.
    0 installs
63. ▌
    Conda Environment Setup And Activation · holobiomicslab

    Use when preparing a fresh system or user account to run MSIGen for mass spectrometry imaging data processing, or when you need to isolate MSIGen installation from other Python projects to avoid dependency conflicts.
    0 installs
64. ▌
    Conditional Execution Dispatch Routing · holobiomicslab

    Use when when you have a Streamlit workflow application that must support both offline (local machine, Windows installer) and online (Docker, cloud) deployment modes, and you need to decide at runtime whether to queue jobs remotely via Redis or spawn local processes.
    0 installs
65. ▌
    Converter Response Parsing And Merging · holobiomicslab

    Use when after executing asynchronous conversion jobs across multiple external APIs during spectrum metadata enrichment, when you have received response dictionaries from one or more converters and need to integrate them into spectrum records while maintaining data integrity and handling partial or.
    0 installs
66. ▌
    Correlation Network Construction Omics · holobiomicslab

    Use when when you have a feature abundance table (rows=features, columns=samples) with >10,000 features from microbiome, metabolomics, transcriptomics, or multi-omics data and need to identify correlated or co-occurring features for network-based analysis, module detection, or cross-omics.
    0 installs
67. ▌
    Cross Platform Build Environment Setup · holobiomicslab

    Use when when you have a Qt5 C++ project (such as Maven GUI or Maven Core) that must be built on multiple target operating systems, and you need to install and verify platform-specific build dependencies (MSYS2 + mingw64 on Windows, Homebrew + Qt5 on macOS, PPA + Qt5.
    0 installs
68. ▌
    Cross Validation Result Interpretation · holobiomicslab

    Use when after running k-fold repeated cross-validation on a development set (via runCrossValidation with parameters k, repNum, and a subset of algorithms) and you need to select which trained classifier and hyperparameter combination to deploy.
    0 installs
69. ▌
    Data Quality Control Report Generation · holobiomicslab

    Use when after applying biomolecule filtering criteria (minimum non-missing values and coefficient of variation thresholds) to an omics expression dataset, generate a report to document filtering impact and justify data retention decisions to stakeholders or for reproducibility.
    0 installs
70. ▌
    Deep Learning Model Weight Persistence · holobiomicslab

    Use when you are training a deep learning model using k-fold cross-validation on an HPC cluster with SLURM job arrays, where each fold runs as a separate independent job with its own GPU allocation.
    0 installs
71. ▌
    Differential Lipid Expression Analysis · holobiomicslab

    Use when when you have a LipidomicsExperiment object with logged and normalized Area measurements, sample grouping metadata (e.g., SampleType, Stage, Race), and a research question about whether specific lipid molecules or classes differ significantly between two or more sample groups.
    0 installs
72. ▌
    Embedding Space Rationality Validation · holobiomicslab

    Use when after training a deep learning model (e.g. MSBERT) on mass spectra and obtaining embedding vectors, apply this skill to verify that the learned representations cluster chemically similar compounds together and that structural relationships are preserved in the embedding space.
    0 installs
73. ▌
    Error Handling For Unsupported Formats · holobiomicslab

    Use when building a file format dispatcher or initialization routine that must accept user-provided file paths and map them to format-specific processing modules.
    0 installs
74. ▌
    Feature Abundance Correlation Grouping · holobiomicslab

    Use when after performing retention-time-based feature grouping (e.g., 10–20 second windows), when you observe large feature groups that may conflate multiple independent compounds with coincidentally similar retention times.
    0 installs
75. ▌
    Feature Interpretation Neural Networks · holobiomicslab

    Use when you have trained multiple neural network models (e.
    0 installs
76. ▌
    Foundation Model Prediction Generation · holobiomicslab

    Use when you have a pre-trained foundation model checkpoint (e.g., NaFM.ckpt) and new molecules represented as SMILES strings or a CSV file, and you need to generate predictions (e.g., bioactivity scores, taxonomy class, screening rankings) or embeddings for downstream analysis.
    0 installs
77. ▌
    Gene Expression Constraint Integration · holobiomicslab

    Use when when you have a generic constraint-based metabolic model, RNA-seq or transcriptomics data (FPKM or similar), and you want to reduce the underdetermination of metabolic flux predictions by encoding which reactions are expected to be active or inactive based on their constituent enzymes'.
    0 installs
78. ▌
    Gene Identifier Format Standardization · holobiomicslab

    Use when when you have differential expression results from genes, miRNAs, proteins, or lipids with heterogeneous identifier formats (raw gene names, Ensembl accessions, RefSeq IDs, or gene symbols) and need to perform pathway enrichment analysis.
    0 installs
79. ▌
    Gene Ontology Enrichment Visualization · holobiomicslab

    Use when you have completed a GO enrichment analysis (e.g., via hypergeometric test or similar) and need to visualize the results as a dotplot. Input is a CSV table with columns for GO term identifiers, p-values or adjusted p-values, gene ratios (or counts), and gene count;
    0 installs
80. ▌
    Hit Score Consolidation Across Domains · holobiomicslab

    Use when you have executed batch spectral searches against two or more domain-specific MASSTs (via the Fast Search API or individual MASST tools) and need to combine the resulting hit lists, match scores, and taxonomic/metadata annotations into a single ranked table for downstream analysis.
    0 installs
81. ▌
    Image Channel Masking And Segmentation · holobiomicslab

    Use when when you have multi-channel LA-ICP-MS images and need to isolate specific elemental regions (e.
    0 installs
82. ▌
    Interactive Plot Generation And Export · holobiomicslab

    Use when after normalizing a featuredata matrix (samples × metabolites), when you need to visually assess the success of normalization across batches or sample groups.
    0 installs
83. ▌
    Internal Standard Intensity Extraction · holobiomicslab

    Use when you have lipidomics data from LipidSearch or LIQUID output that includes internal lipid standards spiked into samples at known concentrations, and your goal is to convert relative intensities to absolute concentration values.
    0 installs
84. ▌
    Metabolite Annotation Ensemble Ranking · holobiomicslab

    Use when you have ESI/LC-MS test spectra requiring candidate metabolite ranking, pre-trained MLP (NEIMS) and GNN baseline models are available or can be trained, you seek quantified improvement over single-model average rank performance (baseline MLP shows ~339 average rank), and your evaluation.
    0 installs
85. ▌
    Metabolite Annotation Mlp Gnn Ensemble · holobiomicslab

    Use when you have ESI/LC-MS test spectra requiring metabolite annotation and need to compare ensemble-based neural network predictions (ESP) against a baseline MLP model to quantify performance gains.
    2 installs
86. ▌
    Metabolite Rank Performance Evaluation · holobiomicslab

    Use when after training an ensemble model (MLP, GNN, or ESP) on spectral data, use this skill to measure performance on test spectra where ground-truth metabolite identities are known. Essential for comparing model variants (e.
    2 installs
87. ▌
    Metabolomics Workflow Step Enumeration · holobiomicslab

    Use when when initializing a SmartPeak session and you have a workflow.csv file co-located with sequence.csv in the session directory, and you need to determine the precise order and validity of peak detection, calibration, and QC operations before execution.
    0 installs
88. ▌
    Molecular Spectrum Prediction Baseline · holobiomicslab

    Use when you have multiple mass spectrum prediction models to compare and need to establish a level playing field by implementing at least one well-characterized baseline (such as NEIMS) with both FFN and GNN encoder variants.
    0 installs
89. ▌
    Molecular Weight Prediction From Ei Ms · holobiomicslab

    Use when you have EI-MS spectrum data (m/z and intensity pairs) from a sample and need a direct, model-based prediction of molecular weight.
    0 installs
90. ▌
    Neutral Loss Annotation Interpretation · holobiomicslab

    Use when when building Word2Vec or embedding-based spectral similarity models where you need to capture fragmentation patterns beyond individual peak positions.
    0 installs
91. ▌
    Overlapped Peak Resolution Transformer · holobiomicslab

    Use when when GC-MS chromatograms contain overlapped or co-eluting peaks in a retention time region and you need to recover the individual pure mass spectra and relative abundances of each component without manual peak picking or external standards.
    0 installs
92. ▌
    Peak Filtering And Preprocessing Lc Ms · holobiomicslab

    Use when you have raw LC-MS/MS spectra from vendor instruments (mzML, mzXML, MGF, or MSP format) with variable peak quality and intensity distributions, and you plan to perform library matching, molecular networking, or spectral similarity comparison.
    0 installs
93. ▌
    Pytorch Model Loading And Forward Pass · holobiomicslab

    Use when when you have a pre-trained PyTorch model checkpoint (e.g., a MWFormer transformer) and structured input data (e.g., electron ionization mass spectrum m/z and intensity pairs) that must be converted to tensor format and passed through the model to produce a direct numerical output (e.
    0 installs
94. ▌
    Retention Time Prediction Optimization · holobiomicslab

    Use when when you have a retention-time dataset (e.g., SMRT or Eawag_XBridgeC18_364) in .xlsx format and need to train or adapt a graph neural network model to predict chromatographic retention times for new compounds.
    0 installs
95. ▌
    Train Validation Test Split Management · holobiomicslab

    Use when when you have a complete dataset of labeled examples (e.g., 100,000 augmented spectra, chromatograms, or synthetic samples) and need to train a supervised model (such as a Transformer) while preserving a held-out test set to measure generalization performance without bias.
    0 installs
96. ▌
    Unsupervised Pattern Discovery Spectra · holobiomicslab

    Use when when you have preprocessed mass spectral data (normalized peak intensities or binned m/z representations) and need to discover latent spectral patterns to enhance neural network predictors without labeled spectral classes.
    2 installs
97. ▌
    Adduct Fragment Formula Interpretation · holobiomicslab

    Use when after temporal correlation has identified candidate feature pairs with matching intensity profiles across time-resolved DBDI-MS experiments.
    0 installs
98. ▌
    Analyte Metadata Hierarchical Indexing · holobiomicslab

    Use when after applying a stringent Q-value quality filter (e.
    2 installs
99. ▌
    Area Integration From Detection Output · holobiomicslab

    Use when you have region-of-interest (ROI) LC-MS data and a pre-trained object detection model has already predicted peak locations and confidence scores.
    0 installs
100. ▌
     Baseline Noise Estimation Chromatogram · holobiomicslab

     Use when after auditing and optionally rescaling a mass track (composite mass chromatogram) when you need to subtract background signal and set dynamic prominence thresholds for peak detection.
     0 installs