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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Noise Threshold Filtering Spectral Data · holobiomicslab

   Use when working with raw IM-MS data (Agilent MassHunter .d or UIMF format) that contains low-abundance background noise, isolated high-intensity artifacts, or jagged peaks characteristic of low-abundance ions.
   0 installs
2. ▌
   Normalized Enrichment Score Computation · holobiomicslab

   Use when you have differential analysis results (p-values and log2 fold changes) from metabolomics data and need to assess whether predefined sets of metabolites (metabolic pathways) show coordinated enrichment patterns.
   0 installs
3. ▌
   Omics Network Visualization Preparation · holobiomicslab

   Use when after constructing a correlation-based network from omics data (nodes and edges defined), when you need to assign visual positions to nodes for rendering.
   0 installs
4. ▌
   Over Representation Enrichment Analysis · holobiomicslab

   Use when you have p-values and effect sizes from two independent association studies (metabolomic GWAS and meta-genome GWAS) and want to identify whether variants associated with disease phenotypes co-occur with metabolites that share biochemical pathways or protein interactions.
   0 installs
5. ▌
   Pairwise Similarity Matrix Construction · holobiomicslab

   Use when after XCMS feature detection and retention time correction, when you have a feature abundance table aligned across samples and need to group features that likely arise from the same compound before downstream annotation.
   0 installs
6. ▌
   Pearson Correlation Statistical Testing · holobiomicslab

   Use when when you have two co-registered LA-ICP-MS element images and need to determine whether the spatial distribution of one element correlates significantly with another.
   0 installs
7. ▌
   Pixel Replacement With Local Statistics · holobiomicslab

   Use when lA-ICP-MS image data contains isolated spike outliers (single or few pixels with anomalously high or low intensities relative to their local neighborhood) that distort quantitative analysis or visualization.
   0 installs
8. ▌
   Python Binding Generation With Nanobind · holobiomicslab

   Use when when you have a C++ library (such as OpenMS) with nanobind binding specifications in a designated bindings directory and need to create a Python module that exposes C++ classes, functions, and data types to Python code.
   0 installs
9. ▌
   Python Dependency Management With Conda · holobiomicslab

   Use when you have a requirements file (e.g., jestr_requirements.
   0 installs
10. ▌
    Qc Sample Filtering Multi Step Criteria · holobiomicslab

    Use when after feature extraction from XCMS, MS-Dial, or similar tools (producing a feature intensity matrix with samples in rows and compounds in columns), and after sample type annotation (blank, curve, qc, unknown).
    0 installs
11. ▌
    R Tibble Object Creation And Validation · holobiomicslab

    Use when when you have raw metabolomics results from multiple studies in heterogeneous file formats (xls/xlsx, csv, or txt) and need to harmonize them into a single, machine-readable tibble structure with required columns (compound identifier, p-value, fold-change, study size N, reference) for.
    0 installs
12. ▌
    Relative Standard Deviation Computation · holobiomicslab

    Use when when you have preprocessed metabolomics data with pooled QC samples and assigned internal standards, and need to select the optimal internal standard for each compound by comparing ratio stability across candidate standards.
    0 installs
13. ▌
    Signal Anomaly Detection Chromatography · holobiomicslab

    Use when you have raw total ion current (TIC) traces extracted from mass spectrometry samples (e.g., from qTOF, orbitrap, or FTICR instruments) and need to identify and flag scans with anomalous peak intensities before feature detection.
    0 installs
14. ▌
    Small Molecule 3d Structure Preparation · holobiomicslab

    Use when when you have ionized adduct structures (SMILES or MOL format) from a prior ionization-state determination step and need to create multiple low-energy 3D conformations before filtering with machine-learning potentials (ASE-ANI) or quantum calculations.
    0 installs
15. ▌
    Smiles Formula Representation Chemistry · holobiomicslab

    Use when when obtaining transformation products through mixed algorithmic backends (library, CTS, BioTransformer, metabolic logic rules) that require different chemical representations: structure-based algorithms need SMILES strings with optional log P values, while formula-based algorithms need.
    0 installs
16. ▌
    Software Distribution File Organization · holobiomicslab

    Use when you have edited one or more core algorithm scripts (Modular.r, genEIC.r, MS1Spectragen.r, or Stats.R) in a shared developer repository (e.g., Core-Match on GitHub) and need to integrate those changes into an already-installed LipidMatch-4.2 or FluoroMatch distribution on disk.
    0 installs
17. ▌
    Spatial Segmentation Shrunken Centroids · holobiomicslab

    Use when apply SSC when you have preprocessed and normalized MS imaging data (e.g., after TIC normalization and peak processing) and need to discover spatially distinct metabolite regions without prior tissue annotation.
    0 installs
18. ▌
    Spectrum Metadata Extraction Validation · holobiomicslab

    Use when when ingesting heterogeneous MS spectral data from multiple open-access libraries (OMS libraries) where metadata completeness and correctness are uncertain.
    0 installs
19. ▌
    Statistical Model Ranking And Selection · holobiomicslab

    Use when you have trained multiple machine learning algorithms (e.
    0 installs
20. ▌
    Structure Organism Consistency Checking · holobiomicslab

    Use when after curating structure-organism pairs from multiple source databases (1_curating stage), when you need to filter curated pairs into high-confidence subsets for downstream analysis.
    0 installs
21. ▌
    Summarizedexperiment Assay Manipulation · holobiomicslab

    Use when when working with multi-batch metabolomics studies where you need to create intermediate normalized assays (e.
    0 installs
22. ▌
    Table Consolidation And Denormalization · holobiomicslab

    Use when when you have cleaned, normalized organism, structure, and reference tables from separate cleaning pipelines (e.g., after 2_curating stage) and must integrate them into a single queryable table while maintaining referential integrity and generating lookup dictionaries.
    0 installs
23. ▌
    Targeted Peak Detection And Integration · holobiomicslab

    Use when you have centroided LC–MS data in .mzML format, a validated table of target compounds with adjusted expected retention times (RT in minutes), and you need to extract peak areas and quality metrics across all sample runs.
    0 installs
24. ▌
    Training Metric Monitoring Torchmetrics · holobiomicslab

    Use when during supervised model training loops when you need to log loss and validation metrics at each epoch to assess whether the model is learning properly and to determine when to stop training.
    0 installs
25. ▌
    Trust Score Propagation Directed Graphs · holobiomicslab

    Use when you have (1) a directed edge list representing a global network (e.
    0 installs
26. ▌
    Genome Scale Metabolic Flux Modeling Workflow · holobiomicslab bundle

    Use when you have a genome-scale constraint-based metabolic model (GEM, SBML/JSON) for one or more organisms and want predicted flux states grounded in your own omics data — integrate transcriptomics / metabolomics-derived constraints (eFlux-style Reaction Activity/Propensity Scores, extracellular uptake-secretion rates) into the model, sample the feasible flux space with optGpSampler, interpret and compare the resulting flux distributions across samples or conditions, and, when multiple organism or community-member models exist, gap-fill and merge them into a consensus community model (COMMIT-style) — connecting metabolomics features to predicted flux states.
    0 installs
27. ▌
    Chain Pruning Threshold Optimization · holobiomicslab

    Use when when comparing mapped read counts between two RNA-seq quantification implementations (e.
    0 installs
28. ▌
    Gene Expression Matrix Normalization · holobiomicslab

    Use when when you have raw or unnormalized gene expression data from microarray experiments (e.
    0 installs
29. ▌
    Log Fold Change Shrinkage Estimation · holobiomicslab

    Use when after running DESeq() and extracting base results with results(), apply shrinkage when you have differential expression estimates and want to reduce the variance of log fold change estimates while preserving signal.
    0 installs
30. ▌
    Method Comparison Differential Calls · holobiomicslab

    Use when you have applied two or more competing analysis workflows to the same RNA-seq or microarray dataset and need to assess whether they yield consistent or divergent differential expression results. Typical triggers: (1) comparing a new normalization method (e.
    0 installs
31. ▌
    Overdispersion Estimation Validation · holobiomicslab

    Use when after using edgeR::DGEListFromTximport with divide=TRUE on tximport output containing Gibbs sample or bootstrap replicates.
    0 installs
32. ▌
    Precision Weight Calculation Rna Seq · holobiomicslab

    Use when you have raw RNA-seq read counts and a set of normalization factors (e.g., TMM-computed library size scales from edgeR's calcNormFactors), and you plan to fit a linear model to detect differential expression.
    0 installs
33. ▌
    Psi Matrix Loading And Normalization · holobiomicslab

    Use when you have generated PSI matrices for alternative splicing events or transcripts across two or more biological conditions using SUPPA's psiPerEvent or psiPerIsoform subcommand, and you need to align and standardize these matrices with corresponding transcript expression quantification files.
    0 installs
34. ▌
    Selective Alignment Parameter Tuning · holobiomicslab

    Use when you observe discrepancies in mapping rate or per-transcript quantification between two salmon implementations, or when the default chain-pruning thresholds (orphanChainSubThresh, postMergeChainSubThresh) are leaving a substantial fraction of reads unmapped (e.
    0 installs
35. ▌
    Group Wise Chemical Enrichment Calculation · holobiomicslab

    Use when when comparing GNPS chemical annotations across two or more groups of samples (defined by ReDU sample-information categories such as sample type, extraction method, or ionization source) where the groups contain different numbers of files.
    0 installs
36. ▌
    Interactive Spectral Visualization Emperor · holobiomicslab

    Use when when you have computed PCA coordinates from chemical annotation matrices (e.
    0 installs
37. ▌
    Mass Spectrometry Library Search Retrieval · holobiomicslab

    Use when when you have an unknown MSMS spectrum (precursor m/z and fragment ions) and need to discover structurally related compounds from a spectral library.
    0 installs
38. ▌
    Peak Detection And Boundary Identification · holobiomicslab

    Use when when you have CE-MS raw data (mzML or netCDF format) with extracted ion traces for target compounds and need to identify peak boundaries and extract quantitative peak properties (retention time on µeff scale, peak intensity, peak area) within a specified mobility window.
    0 installs
39. ▌
    Sodium Adduct Detection And Classification · holobiomicslab

    Use when analyzing MALDI-mass spectrometry imaging data in which sodium or other alkali metal contamination is suspected, or when peak lists show unexplained mass differences in the range of ~20–25 Da (characteristic of Na adducts).
    0 installs
40. ▌
    Spectral Library Annotation Interpretation · holobiomicslab

    Use when you have received chemical annotations from GNPS spectral library matching and need to (1) assess annotation confidence and validity for downstream analysis, (2) understand why the same chemical may appear under multiple GNPS annotation IDs, or (3) decide whether to collapse or deduplicate.
    0 installs
41. ▌
    Tabular Results Aggregation And Comparison · holobiomicslab

    Use when when you have chemical annotations (GNPS matches) distributed across multiple sample groups (e.g., by sample type, extraction method, ionization source) with unequal numbers of files per group, and you need to compare enrichment fairly without group-size bias.
    0 installs
42. ▌
    Compound Structural Fingerprint Comparison · holobiomicslab

    Use when you have a set of query chemicals and a reference library (organized by type or group), and you need to determine which reference compounds most closely resemble each query chemical based on structural features.
    0 installs
43. ▌
    Gc Ms Data Preprocessing And Normalization · holobiomicslab

    Use when you have raw GC-MS data (aroma, breath, or other volatile analyte samples) in NetCDF or vendor-native format and need to identify multivariate chemo-/biomarker features without conventional peak picking.
    0 installs
44. ▌
    Imaging Mass Spectrometry Characterization · holobiomicslab

    Use when you have raw mass spectrometry data files (mzML, NetCDF, or vendor formats) with unknown or mixed acquisition modalities, and you need to automatically determine whether the input is LC-MS, GC-MS, IMS (ion mobility spectrometry), or MS imaging (e.
    0 installs
45. ▌
    Left Censored Missing Value Classification · holobiomicslab

    Use when you have a metabolomics dataset (LC/MS or GC/MS) with missing values and need to determine which are below the limit of detection (LOD) or limit of quantification (LOQ). Left-censored classification is necessary when the missingness is informative—i.
    0 installs
46. ▌
    Metabolomics Imputation Method Application · holobiomicslab

    Use when your metabolomics dataset (LC/MS or GC/MS) contains missing values encoded as NA or zero that represent compounds below the instrument's limit of detection (LOD) or limit of quantification (LOQ), rather than values missing completely at random.
    0 installs
47. ▌
    Multi Task Attention Mechanism Integration · holobiomicslab

    Use when when baseline MLP or GNN models for spectral prediction show limited performance on metabolite annotation tasks, and you have access to auxiliary spectral topic labels (e.g., via LDA on spectral features) that could provide regularization signal.
    0 installs
48. ▌
    Software Architecture Documentation Review · holobiomicslab

    Use when you need to verify the scope and completeness of a software platform's analytical capabilities—particularly when the project claims to support multiple input modalities (e.
    0 installs
49. ▌
    Spectral Database Integration And Sampling · holobiomicslab

    Use when you need to generate synthetic LC/GC-MS feature tables or raw mzML files with realistic peak complexity, ion multiplicities, and natural spectral variation—not just theoretical m/z values.
    0 installs
50. ▌
    Spectral Library Merging And Deduplication · holobiomicslab

    Use when when building a comprehensive reference spectral library for metabolomics or chemical identification, you have multiple source libraries in different formats (msp, mgf, NIST binary) and ionization modes (positive/negative MS/MS or EI) that need to be combined into a single.
    0 installs
51. ▌
    Spectral Vector Normalization By Intensity · holobiomicslab

    Use when when converting pre-processed MS/MS spectra into fixed-length vector representations using Word2Vec embeddings for Spec2Vec similarity scoring. Specifically, apply this skill after you have represented individual peaks and neutral losses as words ('[redacted-email]', 'loss@xxx.
    0 installs
52. ▌
    Background Ion Drift Detection And Removal · holobiomicslab

    Use when processing MS-DIAL peak lists from untargeted LC-MS/MS experiments (DDA or DIA mode) where you suspect instrumental background contamination or ion source carry-over is generating false positive features.
    0 installs
53. ▌
    Batch Preparation Class Imbalance Handling · holobiomicslab

    Use when when you have raw mzML files and a feature table (CSV from mzMine or XCMS) with labeled peaks of unequal class sizes (e.g., fewer false positives than true positives) and plan to train a CNN classifier on the LCMS data.
    0 installs
54. ▌
    Chemical Formula Subformula Classification · holobiomicslab

    Use when you have tandem mass spectra with known molecular structures (SMILES, InChI, or chemical formula) and aim to train or evaluate a formula-level spectrum predictor.
    0 installs
55. ▌
    Chromatographic Data Structure Abstraction · holobiomicslab

    Use when when ingesting raw mass spectrometry data from multiple instrument vendors or file formats into a metabolomics processing pipeline, and you need to expose spectral and chromatographic metadata through a single, consistent interface regardless of the source format's internal structure.
    0 installs
56. ▌
    Chromatographic Profile Quality Assessment · holobiomicslab

    Use when running targeted peak detection on LC-MS data acquired with multiple overlapping m/z scan windows and observing distorted or periodically discontinuous peak profiles in EIC plots.
    0 installs
57. ▌
    Chromatographic Window Coverage Assessment · holobiomicslab

    Use when after extracting retention times from top MS1 features detected in an LC-MS run, and when you need to evaluate whether a given gradient time range (e.g., 0–30 minutes) is being used efficiently to separate compounds. Apply this skill as the objective function in gradient optimization (e.
    0 installs
58. ▌
    Classification Algorithm Tuning Validation · holobiomicslab

    Use when you have labeled training data (e.g., pqm_development with 500 peaks and 89 samples) and need to select which of multiple classification algorithms (e.g., AdaBoost, Random Forest, SVM) and their hyperparameters (e.
    0 installs
59. ▌
    Cnn Transformer Hybrid Architecture Design · holobiomicslab

    Use when when you need to detect and classify peaks in LC-MS regions of interest (ROIs) and simultaneously localize their boundaries for area integration.
    0 installs
60. ▌
    Contrastive Loss Integration With Encoders · holobiomicslab

    Use when you have a transformer encoder producing representations of tandem mass spectra and need to train it using contrastive learning with pairs of original and randomly masked spectra.
    0 installs
61. ▌
    Cross Sample Alignment Matrix Construction · holobiomicslab

    Use when you have already generated per-sample MS2 fingerprints (count vectors of MS2 peaks and neutral losses to the precursor) from matchms-processed spectra using spec2vec document representations, and you need to align these fingerprints into a single matrix to enable comparison across samples.
    0 installs
62. ▌
    Deep Learning Model Inference On Test Sets · holobiomicslab

    Use when you have a pretrained deep learning model, a reserved test set with ground-truth annotations, and need to evaluate prediction quality or generate embeddings for downstream analysis. Typical triggers: benchmarking a new model against classical baselines (e.
    0 installs
63. ▌
    Deep Learning Model Loading And Prediction · holobiomicslab

    Use when when you have preprocessed MS/MS spectral data (normalized peak intensities and m/z values) and need to convert each spectrum into a learned molecular embedding vector for downstream matching against a reference database.
    0 installs
64. ▌
    Deep Learning Model Training And Inference · holobiomicslab

    Use when you have paired tandem MS/MS spectra with known molecular fingerprints, chemical formulae, or SMILES annotations, and you want to learn a generalizable model that can predict molecular properties or annotate unknown spectra by ranking candidates.
    0 installs
65. ▌
    Electronic Noise Detection In Mass Spectra · holobiomicslab

    Use when you have raw MS/MS peak lists and suspect electronic noise contamination—particularly when peaks show repeated, identical intensity values across multiple m/z entries within a single spectrum, which are rare in genuine biological spectra but common in instrument artifacts.
    0 installs
66. ▌
    Embedding Space Normalization And Geometry · holobiomicslab

    Use when when designing a Siamese or multi-branch neural architecture where two or more embedding streams (e.
    0 installs
67. ▌
    Feature Occurrence Counting Across Spectra · holobiomicslab

    Use when when you have parsed MS2 spectra from a single metabolomics sample (via matchms or similar) and need to generate a sample-level feature vector that represents the chemical composition independently of chromatographic alignment.
    0 installs
68. ▌
    Filter Criteria Composition And Validation · holobiomicslab

    Use when you are preparing to reuse public tandem MS data from MassIVE via ReDU and need to partition files by sample metadata (e.g., organism, tissue type, extraction method, ionization source, pre-MS separation) into groups for co-analysis.
    0 installs
69. ▌
    Graph Neural Network Architecture Assembly · holobiomicslab

    Use when when you have: (1) a collection of molecules represented as molecular graphs (nodes=atoms, edges=bonds with chirality/order attributes); (2) structured metadata describing experimental conditions (e.
    0 installs
70. ▌
    Hierarchical Library Data Structure Design · holobiomicslab

    Use when when building a reference library for high-throughput spectral matching against experimental MS/MS data, and you need to support millions to billions of queries per second on a standardized dataset.
    0 installs
71. ▌
    High Quality Spectral Library Benchmarking · holobiomicslab

    Use when you have a pre-trained MS/MS spectral embedding model and need to validate that it achieves strong and consistent retrieval performance on curated spectral libraries that represent real-world data quality standards.
    0 installs
72. ▌
    Inchikey Structural Similarity Computation · holobiomicslab

    Use when you have a ranked list of library candidates (top 2000 by MS2Deepscore) from MS/MS spectral matching and need to re-rank them using structural metadata to distinguish true analogues and exact matches from false positives.
    0 installs
73. ▌
    Ionization Mode And Column Mode Separation · holobiomicslab

    Use when your LC-MS peak table from MS-DIAL or similar software contains data from multiple ionization modes (positive and/or negative) and/or multiple chromatographic columns (e.
    0 installs
74. ▌
    Ionization Mode Merging And Reconciliation · holobiomicslab

    Use when you have acquired MS-DIAL peak lists in both positive and negative ionization modes on the same sample set and want to consolidate detected features across modes to avoid reporting duplicate annotations for the same molecule.
    0 installs
75. ▌
    Isotopic Signature Clustering And Grouping · holobiomicslab

    Use when you have a feature table (m/z, drift_time, retention_time, intensity) from LC-IMS-MS or similar multi-dimensional MS acquisition and need to (1) link isotopic variants to their monoisotopic parent features, (2) disambiguate true chemical features from noise or instrumental artifacts, or.
    0 installs
76. ▌
    Isotopic Signature Detection And Filtering · holobiomicslab

    Use when after DEIMoS isotope detection has assigned potential isotopic signatures to detected features in aligned MS1 data.
    0 installs
77. ▌
    Latent Dirichlet Allocation Model Training · holobiomicslab

    Use when when you have preprocessed MS/MS spectral data (filtered, noise-reduced, with neutral losses extracted) and need to discover recurring fragmentation patterns across a spectral dataset.
    0 installs
78. ▌
    Mass Spectrometry Base Peak Identification · holobiomicslab

    Use when after PuInc_seeker has identified putative incorporations in XCMS-processed LC/MS data, when you have paired unlabeled and labeled sample groups (e.
    0 installs
79. ▌
    Mass Spectrometry Data Statistical Testing · holobiomicslab

    Use when you have a normalized abundance matrix from LC-MS/MS profiling with sample class assignments (e.g., phenotypic groups, disease states, treatment conditions) and need to filter metabolic features for downstream pathway analysis or biological validation.
    0 installs
80. ▌
    Mass Spectrometry Ionization Mode Handling · holobiomicslab

    Use when when you have a feature table from LC-MS preprocessed data (e.g. from asari v1.9.2) and need to annotate ions and infer neutral mass.
    0 installs
81. ▌
    Mass Spectrometry Precursor Identification · holobiomicslab

    Use when when you need to locate and extract quantitative retention time and intensity data for known peptide standards (e.g., iRT peptides) from a Thermo .raw file to validate LC-MS retention time linearity, assess method reproducibility, or establish retention time calibration curves.
    0 installs
82. ▌
    Mass To Charge Ratio Matching Against Kegg · holobiomicslab

    Use when you have an LC-MS peak-intensity matrix (rows = peaks with m/z and intensity; columns = samples) and need to assign KEGG compound identifiers to observed peaks.
    0 installs
83. ▌
    Metabolite Annotation Network Architecture · holobiomicslab

    Use when when annotating large-scale untargeted metabolomics datasets where reference library coverage is incomplete and you need to infer metabolite identities for unannotated compounds by propagating annotations from seed metabolites (database matches or prior curation) across both.
    0 installs
84. ▌
    Metabolite Candidate Ranking By Confidence · holobiomicslab

    Use when you have a set of candidate metabolites for an unknown compound detected in a liquid chromatography–mass spectrometry (LC-MS) experiment, predicted RTs from a trained DNN model, and access to calibration molecules (minimum 10) that connect your observed chromatographic method to a source.
    0 installs
85. ▌
    Metabolite Feature Intensity Normalization · holobiomicslab

    Use when after imputation and batch-effect correction (OUKS steps 3–4) have been completed on your LC-MS feature-intensity table, and before statistical hypothesis testing.
    0 installs
86. ▌
    Metabolite Fold Change Statistical Testing · holobiomicslab

    Use when you have XCMS-processed LC/MS peak data from dual-labeled (e.g., 13C) and unlabeled (12C) metabolomics samples and need to distinguish features genuinely enriched by stable isotope incorporation from noise or background variation.
    0 installs
87. ▌
    Metabolite Structural Network Construction · holobiomicslab

    Use when after MamsiStructSearch has completed structural clustering of statistically significant LC-MS features (p < 0.
    0 installs
88. ▌
    Metabolomics Feature Extraction And Export · holobiomicslab

    Use when you have raw LC-MS data (mzXML format or pre-computed feature tables from external software) and need to: (1) detect both Gaussian and non-Gaussian shaped metabolic features across multiple samples, (2) align these features across samples, and (3) export EIC chromatograms with m/z.
    0 installs
89. ▌
    Metabolomics Noise Perturbation Simulation · holobiomicslab

    Use when when benchmarking or validating a pathway analysis method (such as PALS, ORA, or GSEA) on metabolomics data, you need quantitative evidence that the method's pathway rankings remain stable despite noise and missing peaks—conditions prevalent in real LC-MS/MS datasets.
    0 installs
90. ▌
    Metadata Field Based Sample Stratification · holobiomicslab

    Use when you have a feature table and accompanying CSV metadata that includes a 'Sample Type' field (or equivalent) with entries such as 'BLANK', 'QC', 'STD', or 'Unknown'.
    0 installs
91. ▌
    Missing Value Imputation By Data Recursion · holobiomicslab

    Use when after sample alignment and feature grouping in untargeted LC-MS workflows, when the aligned feature table contains missing intensity values (NA or zero entries) due to features falling below the detection limit in some samples but being present above-threshold in others.
    0 installs
92. ▌
    Modular Fragmentor Interface Configuration · holobiomicslab

    Use when you need to simulate LC-MS/MS spectra for a specific biomolecule type (peptides, modified nucleosides, or other metabolites) and must choose which fragmentation model governs how parent ions break into fragment ions.
    0 installs
93. ▌
    Ms Ms Spectral Preprocessing Noise Removal · holobiomicslab

    Use when when you have raw MS/MS spectra (from NIST, MassBank, or local acquisition) and plan to compute spectral similarity for compound identification.
    0 installs
94. ▌
    Ms Ms Spectral Preprocessing Normalization · holobiomicslab

    Use when you have paired MS/MS spectra from unknown and known metabolites with raw intensity values and need to prepare them as input for a deep-learning model that will predict structural similarity.
    0 installs
95. ▌
    Multi Head Attention Mechanism Application · holobiomicslab

    Use when you have embedded sequences of chemical formulae (tokenized and converted to dense vectors) from tandem MS/MS spectra and need to learn context-dependent representations that capture dependencies between formula tokens at multiple semantic levels.
    0 installs
96. ▌
    Multi Sample Metabolomics Data Integration · holobiomicslab

    Use when you have two or more independently processed MemoMatrix objects (each generated from a separate sample set) and your analysis goal requires direct comparison of MS2 fingerprint profiles across those samples.
    0 installs
97. ▌
    Multidimensional Spectral Array Extraction · holobiomicslab

    Use when you have multidimensional MS data (with LC and/or ion mobility dimensions) converted to MZA HDF5 format and need to retrieve raw spectral intensity and m/z values for specific scans, retention times, drift times, or mass ranges.
    0 installs
98. ▌
    Neural Network Architecture Design Spectra · holobiomicslab

    Use when you have preprocessed MS/MS spectra pairs (unknown and known metabolites) with annotated structural similarity labels, and you need to learn a generalizable model that can rank candidate structures for novel unknowns by predicting their similarity to reference compounds in a database.
    0 installs
99. ▌
    Non Targeted Preprocessing Tool Comparison · holobiomicslab

    Use when you have LC-HRMS mzML data processed by at least one non-targeted pre-processing tool (XCMS, MZmine 2, MZmine 3, MS-DIAL, OpenMS, El-MAVEN, or similar), you have access to curated retention time boundaries and molecular formulas for a set of known target compounds (ideally 30+ molecules.
    0 installs
100. ▌
     Open Modification Spectral Search Strategy · holobiomicslab

     Use when when searching an unknown query MS/MS spectrum against a large spectral library (>100k spectra) for both unmodified and modified peptides, and computational speed is critical without sacrificing sensitivity or FDR control.
     0 installs