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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Compiled Module Import Verification · holobiomicslab

   Use when after compiling nanobind-based C++ bindings into a Python extension module (e.g., pyOpenMS), or when integrating a newly built native module into a Python environment. Apply this skill to confirm that the generated .so/.pyd/.
   0 installs
2. ▌
   Contrastive Learning Encoder Design · holobiomicslab

   Use when when you have mass spectrometry ion image data and need to learn meaningful low-dimensional representations through self-supervised contrastive learning.
   0 installs
3. ▌
   Cross Instrument Data Harmonization · holobiomicslab

   Use when you have mass spectrometry spectral data from multiple instrument types (e.g., direct infusion MS, ambient ionization MS, laser desorption/ionization MS) and need to perform unified species discrimination or database scoring across all samples regardless of their source instrument.
   0 installs
4. ▌
   Cross Platform Dependency Detection · holobiomicslab

   Use when when developing a standalone scientific application that relies on external binaries or libraries and must run on a specific operating system (e.g., Microsoft Windows 64-bit). Use this skill to verify Gnuplot 5.4.
   0 installs
5. ▌
   Cross Validation Strategy Selection · holobiomicslab

   Use when when preparing to train supervised binary classification models (logistic regression, random forest, XGBoost) on metabolomics datasets in MeTEor, you must first decide between stratified k-fold cross-validation (suitable for larger, balanced cohorts) and leave-one-out cross-validation.
   0 installs
6. ▌
   CSV XLSX File Conversion And Export · holobiomicslab

   Use when when you have validated mass spectrometry transition data (precursor m/z, product m/z, intensity, retention time, and compound identifiers) formatted in one tabular format (CSV or XLSX) and need to convert it to the other format for ingestion into EISA-EXPOSOME or long-term archival.
   0 installs
7. ▌
   Cumulative Distribution Calculation · holobiomicslab

   Use when you have numeric distribution data (e.g., gene expression, abundance, or measurement values) in CSV format and need to compare cumulative empirical distributions either within a single cohort or across multiple sample groups (e.g., control vs. treatment, disease subtype vs. healthy).
   0 installs
8. ▌
   Data Column Recognition And Mapping · holobiomicslab

   Use when when uploading a delimited CSV or similar tabular file to Punc'data containing high-resolution mass spectrometry results, and the column headers are present but their semantic roles (e.
   0 installs
9. ▌
   Data Handoff Pipeline Orchestration · holobiomicslab

   Use when you have raw MS files (with associated metadata: filename, upload path, file format) staged in an uploader repository and need to route them to a proteomics processor for analysis while preserving audit trails and ensuring format compatibility before processing begins.
   0 installs
10. ▌
    Duplicate Spectrum Detection Splash · holobiomicslab

    Use when when processing large collections of mass spectra from multiple Open Mass Spectra Libraries (OMSLs) or databases that may contain redundant spectral records with identical m/z–intensity peak patterns but potentially different metadata annotations.
    0 installs
11. ▌
    Effect Size Calculation Metabolites · holobiomicslab

    Use when after applying statistical tests (e.g., Student's t-test) to identify differentially abundant metabolites between two or more sample groups in a MultiAssayExperiment object.
    0 installs
12. ▌
    Embedding Vector Similarity Ranking · holobiomicslab

    Use when you have a query mass spectrum and need to retrieve the most chemically similar reference spectra from a large experimental or predicted library (thousands to millions of entries).
    0 installs
13. ▌
    Enrichment Statistic Interpretation · holobiomicslab

    Use when after performing two-group or multi-group differential analysis on a lipidomics dataset and obtaining log fold-change (logFC) values for individual lipid molecules, use this skill to determine whether specific lipid classes, chain lengths, or unsaturation patterns are systematically up- or.
    0 installs
14. ▌
    Feature Abundance Table Preparation · holobiomicslab

    Use when you have raw omics data (microbiome OTU/ASV tables, metabolomic or transcriptomic abundance matrices) that needs to be reformatted or validated before correlation analysis.
    0 installs
15. ▌
    Feature Frequency Filtering Imaging · holobiomicslab

    Use when after peak alignment across all spectra in an imaging dataset, use this skill when you have detected many peaks but need to reduce false positives and sparse features.
    0 installs
16. ▌
    Feature Relationship Edge Weighting · holobiomicslab

    Use when after structural clusters have been identified by MamsiStructSearch (via isotopologue, adduct, and cross-assay link detection), and you need to construct a NetworkX graph where edges encode the biochemical relationship type and strength between features for downstream curation.
    0 installs
17. ▌
    Feature Table Export And Validation · holobiomicslab

    Use when after executing an MZmine batch processing workflow on raw metabolomics data (mzML/mzXML format), when you need to convert the in-memory feature detection and alignment results into a shareable, schema-compliant tabular format suitable for downstream statistical analysis, figure.
    0 installs
18. ▌
    Feature Table Subsetting And Export · holobiomicslab

    Use when you have a raw metabolite abundance matrix with substantial missing data (NAs or zero-valued entries) and need to remove poorly-measured features before downstream analysis. Apply this skill when the proportion of missing values per metabolite exceeds a predefined threshold (e.
    0 installs
19. ▌
    Gcf Assignment From Distance Matrix · holobiomicslab

    Use when when you have pre-computed BGC feature vectors (from domain architecture or other representations) and need to group them into functionally coherent GCFs for comparative analysis.
    0 installs
20. ▌
    Genotype Phenotype Data Preparation · holobiomicslab

    Use when when you have raw genotype and phenotype data files (e.g., from a GWAS dataset or genetic study) and need to apply PaIRKAT or similar pathway-level association tests.
    0 installs
21. ▌
    Graph Neural Network Implementation · holobiomicslab

    Use when when your input includes molecular structures (SMILES, conformers) and you need to predict a continuous property (e.g., CCS, binding affinity, solubility) that depends on molecular connectivity and spatial relationships.
    0 installs
22. ▌
    Graph Neural Network Model Training · holobiomicslab

    Use when when you have a molecular dataset (e.g., SMRT retention-time pairs) that you want to model as node-and-edge graphs, a PyTorch + PyG architecture already instantiated, and need to perform supervised training with checkpoint persistence and per-epoch metric logging.
    0 installs
23. ▌
    Gui Widget Filtering Implementation · holobiomicslab

    Use when a GUI widget (e.g., isotopes display, compound list, or metabolite selector) should honor user preferences to show only a subset of available items, and the filtering logic must read from application preferences and apply it during widget rendering or refresh cycles.
    0 installs
24. ▌
    Hierarchical Normalisation Strategy · holobiomicslab

    Use when when you have multiple batches of metabolomics data with embedded intra-batch (short) and inter-batch (batch) replicate samples, visible run-order signal drift in individual metabolites within batches, and batch effects visible in PCA or run plots.
    0 installs
25. ▌
    High Performance Metric Computation · holobiomicslab

    Use when you have implemented or are evaluating an algorithmic or system optimization (e.g., MASST+) that claims to reduce execution time, and you need to quantify and statistically validate the speedup against a baseline system (e.g., MASST).
    0 installs
26. ▌
    Igraph Object Creation Manipulation · holobiomicslab

    Use when after computing pairwise correlations across features (10,000+ in high-dimensional omics datasets) and applying correlation thresholding to retain only significant edges, you need to construct an igraph object that preserves edge weights, supports node annotation, and enables module.
    0 installs
27. ▌
    Interactive Plot Backend Evaluation · holobiomicslab

    Use when you have mass spectrometry data (chromatograms, spectra, peak maps, mobilograms) that you want to visualize interactively using pyOpenMS-viz, and you need to select between bokeh and plotly backends based on execution time and feature parity.
    0 installs
28. ▌
    Jupyter Notebook Development Python · holobiomicslab

    Use when when building reproducible Python-based computational workflows that must serve both beginner and expert users; when the analysis requires interactive parameter tuning, file upload capability, or real-time result visualization;
    0 installs
29. ▌
    Jupyter Notebook Workflow Execution · holobiomicslab

    Use when you have a curated training dataset of molecular structures with known CCS values, a target set of ≤10,000 molecules requiring CCS predictions, and need to apply a pre-configured Sklearn-based machine learning model within a reproducible, browser-accessible environment.
    0 installs
30. ▌
    Jvm Heap Memory Tuning Verification · holobiomicslab

    Use when when deploying the ipbhalle/metfragweb Docker container and you need to confirm that custom JVM heap sizes (specified via JAVA_OPTS=-Xmx?g -Xms?g) have taken effect, or when troubleshooting memory-related runtime issues in the running container.
    0 installs
31. ▌
    Label Propagation Network Algorithm · holobiomicslab

    Use when you have a ranked list of seed genes or metabolites (e.g., from metabolomic enrichment analysis with MSEA scores, or exome-derived candidate genes) and you want to propagate their signals across a gene–protein interaction network (e.
    0 installs
32. ▌
    Lipid Database Query And Annotation · holobiomicslab

    Use when you have parsed MRM transition data (m/z values, retention times, transition parameters) from mass spectrometry experiments and need to map each detected transition to a known lipid identity.
    0 installs
33. ▌
    Lipid Nomenclature Pattern Matching · holobiomicslab

    Use when when loading a lipidomics dataset into lipidr and the parsing step generates warnings about unparsed molecules due to unsupported naming patterns.
    0 installs
34. ▌
    M Z Retention Time Feature Matching · holobiomicslab

    Use when after extracting a feature table from XCMS, MS-Dial, or similar tools, when you possess a reference compound database with known m/z, retention time, and metadata, and you need to assign high-confidence (AnnoLevel 1) compound identities.
    0 installs
35. ▌
    Mass Accuracy Tolerance Application · holobiomicslab

    Use when when you have generated in silico annotations (from GNPS ISDB, SIRIUS, or timaR) and need to distinguish true matches from false positives by enforcing a mass accuracy constraint. Apply this skill before computing novelty metrics (e.
    0 installs
36. ▌
    Mass Spectrometry Adduct Assignment · holobiomicslab

    Use when when processing in-silico or experimental MS spectra records from databases with incomplete metadata, specifically when the adduct field is null or absent but the ionmode field (positive/negative polarity) is present.
    0 installs
37. ▌
    Mass Spectrometry Format Conversion · holobiomicslab

    Use when when you have mass spectrometry spectra in one of the six supported formats (mzML, mzXML, msp, metabolomics-USI, MGF, JSON) and need to convert them to a different format for compatibility with downstream tools, or when importing raw spectra into matchms for the first time and need to.
    0 installs
38. ▌
    Mass Spectrometry Peak Data Loading · holobiomicslab

    Use when when you have raw or parsed MS spectra data (m/z values, intensity values, and spectral metadata) and need to integrate it into a Spectra object for downstream processing.
    0 installs
39. ▌
    Mass Spectrometry Raw File Handling · holobiomicslab

    Use when you have raw MS data files from Thermo Orbitrap or other vendor instruments that must be uploaded into a centralized platform for automated processing. Use it at the start of a multi-stage omics workflow where data collection, management, processing, and visualization are integrated;
    0 installs
40. ▌
    Mass Spectrometry Tune Data Loading · holobiomicslab

    Use when you have positive- or negative-mode tune reference compound data stored in HDF5 format (e.g., example_tune_pos.h5) and need to extract the tune mass spectrum for CCS calibration. This skill is the entry point before applying deimos.calibration.
    0 installs
41. ▌
    Matplotlib Static Figure Generation · holobiomicslab

    Use when you have mass spectrometry data in a pandas DataFrame with retention time (rt) and intensity columns, and need to produce a static figure for publication, presentation, or archival.
    0 installs
42. ▌
    Metabolic Network Edge Construction · holobiomicslab

    Use when when building a comprehensive chemical knowledge base for mass spectrometry formula assignment, particularly when you need to link chemical formulae across heterogeneous repositories (HMDB, ChEMBL, PubChem) and connect them through known metabolic transformations to improve annotation.
    0 installs
43. ▌
    Metabolic Network Topology Encoding · holobiomicslab

    Use when when you have reconstructed metabolic networks for one or more organisms and need to represent them in a way that preserves both the graph topology (connectivity structure) and the metabolic function annotations (pathway membership and enzymatic roles) for subsequent cross-organism.
    0 installs
44. ▌
    Metabolite False Positive Filtering · holobiomicslab

    Use when you have ion-mobility mass spectrometry metabolomics data with putative metabolite identifications (e.g., from database matching) and want to reduce false positives by cross-validating compound identities against machine-learned CCS predictions.
    0 installs
45. ▌
    Metabolite Identifier Cross Mapping · holobiomicslab

    Use when when you have metabolite identifiers from one or more metabolome databases and need to resolve them to equivalent identifiers in other databases, or when standardizing metabolite representation across multi-source metabolomic datasets where compounds may be annotated using different.
    0 installs
46. ▌
    Metabolite Identifier Normalization · holobiomicslab

    Use when your metabolomics dataset contains compound identifiers in mixed formats (chemical names, InChI strings, InChIKey hashes, or SMILES notation) and you need a single canonical identifier to enable meta-analysis across multiple studies or to avoid counting the same metabolite twice under.
    0 installs
47. ▌
    Metabolite Missing Value Imputation · holobiomicslab

    Use when metabolite assay tables contain missing values (NAs) that exceed detection or instrument runtime limits, AND you have retained metabolites with ≥60% non-missing data (i.e., ≤40% missingness).
    0 installs
48. ▌
    Metabolomic Data Quality Assessment · holobiomicslab

    Use when when you have raw metabolomics data with missing values in metabolite columns and need to prepare the dataset for downstream statistical analysis (linear mixed models, ANOVA, dimensionality reduction, or prediction models).
    0 installs
49. ▌
    Metabolomic Peak Quality Assessment · holobiomicslab

    Use when after peak detection in untargeted LC/HRMS workflows, when you have a list of candidate peaks with signal intensity profiles and need to filter them according to data quality thresholds (signal-to-noise ratio, peak width, baseline separation, and isotopic pairing consistency) before.
    0 installs
50. ▌
    Metadata Structure Field Enrichment · holobiomicslab

    Use when a metadata table contains compound names and identifiers but lacks structural data (SMILES, InChI, or molecular formula). The compounds are publicly available in PubChem and can be reliably identified by their chemical names. Use this skill before performing structure-dependent analyses (e.
    0 installs
51. ▌
    Model Weight Loading And Deployment · holobiomicslab

    Use when you have a pre-trained MSGO model checkpoint (PFAS or lipid variant) and need to evaluate it against a real mass spectrometry dataset (300+ real spectra, LC–QTOF, or custom CSV) to generate predicted molecular structures and compare against ground truth or baseline results.
    0 installs
52. ▌
    Molecular Descriptor Interpretation · holobiomicslab

    Use when you have a collection of molecules represented as CSV or EXCEL files containing computed molecular descriptors (e.g., physicochemical properties, structural features) and you need to predict whether each molecule will taste bitter.
    0 installs
53. ▌
    Molecular Formula Search Assignment · holobiomicslab

    Use when you have a recalibrated FT-ICR mass spectrum (Bruker .d format or equivalent) with detected, noise-thresholded peaks and need to assign chemical formulas to each peak. This is particularly relevant when analyzing samples with unknown composition (e.
    0 installs
54. ▌
    Molecular Structure Tensor Encoding · holobiomicslab

    Use when when you have raw molecular structure representations (SMILES strings, InChI notation, or chemical formulas) and need to feed them into a neural spectrum prediction model like SCARF or ICEBERG. Apply this skill before any forward inference pass through a pre-trained spectrum predictor.
    0 installs
55. ▌
    Multi Constraint Metabolic Modeling · holobiomicslab

    Use when you have metabolic models for multiple biological samples and need to distinguish between samples based on their metabolic phenotype, but single constraints (e.g., gene expression alone or nutrient availability alone) fail to segregate them adequately.
    0 installs
56. ▌
    Multimodal Feature Tensor Alignment · holobiomicslab

    Use when when you have molecule IDs converted to multiple independent feature modalities (graph-based node/edge tensors from RDKit, Morgan fingerprints, and computed physicochemical descriptors) and need to combine them into a single structured tensor representation for multimodal model training.
    0 installs
57. ▌
    Network Topology Metric Computation · holobiomicslab

    Use when after constructing or loading a network object (from adjacency matrix, edge list, or correlation output) and needing to quantify structural properties—such as identifying hub nodes via degree centrality, assessing clustering via coefficient distributions, measuring network resilience via.
    0 installs
58. ▌
    Open Modification Spectrum Matching · holobiomicslab

    Use when when you have a query mass spectrum with unknown or unanticipated post-translational modifications and need to match it against an unmodified spectral library.
    0 installs
59. ▌
    P Value And Fold Change Computation · holobiomicslab

    Use when you have raw metabolomics data organized as a matrix with metabolites as rows and samples as columns, sample group labels (e.
    0 installs
60. ▌
    P Value Interpretation Metabolomics · holobiomicslab

    Use when after fitting repeated measures ANOVA models to long-format imputed metabolomics data with a grouping variable (e.g., treatment, disease state) and subject-level random effects.
    0 installs
61. ▌
    Pandas Dataframe Plotting Interface · holobiomicslab

    Use when you have mass spectrometry data (retention time, m/z, intensity, or mobility dimensions) already loaded into a Pandas DataFrame and need to produce publication-ready or exploratory visualizations. Use this when you want to leverage Pandas' native .
    0 installs
62. ▌
    Parent Product Relationship Mapping · holobiomicslab

    Use when you have predicted biotransformation products from BioTransformer's environmental microbial degradation module (or similar rule-based prediction engines) and need to construct traceable lineages showing which parent compound(s) produced which metabolite(s) and what reaction type(s).
    0 installs
63. ▌
    Pathway Level Sample Stratification · holobiomicslab

    Use when you have per-sample metabolite abundance data and a metabolite-to-pathway association table, and need to assign each sample a dysregulation score for each pathway to enable downstream pathway-level classification, feature selection, or survival analysis.
    0 installs
64. ▌
    Pathway Level Statistical Inference · holobiomicslab

    Use when when you have genotype data (variants grouped by pathway annotation) and quantitative or binary phenotype data, and you want to test whether a pathway as a whole is associated with the phenotype, rather than testing individual variants.
    0 installs
65. ▌
    Peak Annotation With Bounding Boxes · holobiomicslab

    Use when you have isolated reference peaks from training chromatograms (ground-truth, single compounds per sample) and need to create a diverse, labelled training set large enough to train a CNN peak detector.
    0 installs
66. ▌
    Peak Center Coordinate Localization · holobiomicslab

    Use when you have LC-HRMS profile mode data with candidate peak regions (local maxima) exported as standardized rt×mz two-dimensional areas, and you need to automatically predict the precise peak-center location (both rt and mz coordinates) rather than relying on manual inspection or simple.
    0 installs
67. ▌
    Peak Integration Quality Assessment · holobiomicslab

    Use when you have a metabolomic feature table (rows=features, columns=samples) with peak height and peak area measurements from chromatographic processing, and you suspect data quality issues such as misaligned features or erratic peak integration across your sample cohort.
    0 installs
68. ▌
    Peptide Sequence Annotation Mapping · holobiomicslab

    Use when you have PSM files from a proteomics search engine (e.g., MaxQuant, MSGFPlus, MS Amanda) and need to convert their native modification notation into HUPO-PSI ProForma v2 format before rescoring. Specifically, use it when: (1) search engines report modifications with custom labels (e.
    0 installs
69. ▌
    Pre Analytical Stability Assessment · holobiomicslab

    Use when you have identified a set of lipid or polar metabolite analytes to measure from blood samples and need to determine whether they will remain stable under your planned or actual pre-analytical handling conditions (time delays before/after centrifugation and processing temperatures).
    0 installs
70. ▌
    Prediction Ensemble Post Processing · holobiomicslab

    Use when you have retention order predictions from multiple trained ROASMI models (e.g., ROASMI_1 through ROASMI_5) for the same set of compounds and need to estimate prediction uncertainty to support small molecule identification.
    0 installs
71. ▌
    Pubchem Compound Database Retrieval · holobiomicslab

    Use when you need to supply candidate metabolite structures for mass spectrometry annotation when working within an integrative metabolomics data analysis workflow (such as MAGMa).
    0 installs
72. ▌
    Python Conda Environment Management · holobiomicslab

    Use when when setting up a multi-language data analysis pipeline that requires both R and Python components to coexist with exact version constraints, especially when deep learning (keras) and machine learning (caret, pROC) packages must share a common Python backend.
    0 installs
73. ▌
    Python Random Access Implementation · holobiomicslab

    Use when when you have an indexed gzip file (mzML.gz with internal index structure) and need to retrieve individual spectra or chromatograms by integer index without decompressing the entire file.
    0 installs
74. ▌
    Pytorch Model Checkpoint Management · holobiomicslab

    Use when you have a pretrained GNN-RT model trained on a reference molecular database and need to adapt it to predict LC retention times on a different in-house molecular dataset with potentially different chromatographic conditions or chemical space.
    0 installs
75. ▌
    Qc Biological Sample Stratification · holobiomicslab

    Use when after metabolomics data normalization when both QC (quality control) and biological samples have been used in the same normalization run.
    0 installs
76. ▌
    Qc Sample Integration Normalization · holobiomicslab

    Use when normalizing multi-batch metabolomics intensity matrices where QC samples are available alongside biological samples, and when you need to detect whether QC samples are representative of the biological population (i.e., whether they follow the same systematic drift).
    0 installs
77. ▌
    Ras Dependent Flux Boundary Setting · holobiomicslab

    Use when when you have a generic constraint-based metabolic model, cell-line-specific or sample-specific transcriptomics data (e.g., FPKM or RNA-seq), and need to generate cell-relative metabolic models that account for differential gene expression.
    0 installs
78. ▌
    Rdkit Molecular Property Extraction · holobiomicslab

    Use when when you have a set of compounds represented as SMILES strings and need to compute their molecular properties (neutral mass, adduct-adjusted masses, mordred descriptors) for comparison against experimental peaks, retention time predictions, or similarity-based filtering thresholds during.
    0 installs
79. ▌
    Regression Model Evaluation Metrics · holobiomicslab

    Use when after training a deep-learning regression model (e.g., for CCS prediction from voxel projected area features), evaluate it on held-out test data to report per-molecule predictions and aggregate performance metrics.
    0 installs
80. ▌
    REST API Query And Response Parsing · holobiomicslab

    Use when you have deployed a TensorFlow Serving instance (via docker-compose or equivalent) and need to verify that the model's input layer names ('input_2048' and 'input_4096') and output layer name ('output') match the expected schema before integrating the model into a classification pipeline or.
    0 installs
81. ▌
    Retention Time Alignment Evaluation · holobiomicslab

    Use when you have run an NPP tool (XCMS, MZmine 2, etc.) on mzML files and need to assess whether the alignment stage preserved peak detection fidelity and isotopologue abundance ratios.
    0 installs
82. ▌
    Retention Time Intensity Extraction · holobiomicslab

    Use when when you have imported mass spectrometry data in .raw, .d, or mzXML format and need to generate a TIC plot to visualize overall sample ionization intensity as a function of retention time.
    0 installs
83. ▌
    Root Developmental Tissue Profiling · holobiomicslab

    Use when you have CDF-format mass spectrometry imaging files from plant roots with accompanying MATLAB workspace files (.mat), and your research goal is to reproduce linear-axis intensity profiles, feature distributions, and spatial metrics reported in a prior publication (e.g., Sama et al. 2025).
    0 installs
84. ▌
    Sample Quality Assessment Using Pca · holobiomicslab

    Use when after loading and basic filtering of (un)targeted metabolomic data (sample/feature missingness, peak area filters) but before aggregation or statistical modeling.
    0 installs
85. ▌
    Script Reproducibility Verification · holobiomicslab

    Use when when you have access to a repository containing simulation scripts (e.g., Type I error and power simulation code) and need to verify that the published findings—specifically reported error rates or power estimates—can be independently regenerated by re-running the deposited code.
    0 installs
86. ▌
    Semantic Version Parsing Comparison · holobiomicslab

    Use when before executing a bioinformatics pipeline that depends on multiple R packages with strict version constraints (e.g., DaDIA, which requires R ≥4.0, XCMS ≥3.11.4, and metaMS =1.25.1).
    0 installs
87. ▌
    Sequence File Inventory Enumeration · holobiomicslab

    Use when when you maintain a repository with local sequence files and need to determine which sequences are not publicly available in NCBI GenBank/RefSeq databases—for example, to distinguish proprietary or supplementary sequence data from publicly registered entries, or to create an inventory.
    2 installs
88. ▌
    Sequence To Sequence Model Training · holobiomicslab

    Use when you have paired multimodal scientific data (e.
    0 installs
89. ▌
    Smiles Sdf Molecule Format Handling · holobiomicslab

    Use when when you have molecular structures in SMILES or SDF format that need to be passed to CyProduct for metabolite prediction, or when you need to switch between string-based and file-based molecular representations for compatibility with different CYP450 enzyme prediction workflows.
    0 installs
90. ▌
    Spatial Transcriptomics Integration · holobiomicslab

    Use when you have paired spatial transcriptomics and spatial metabolomics datasets from the same sample(s) that are at different spatial resolutions or coordinate systems, and you need to integrate them for joint analysis of cross-modal spatial patterns.
    0 installs
91. ▌
    Spectral Database Schema Validation · holobiomicslab

    Use when when you have compiled raw mass spectrometry transition data (precursor m/z, product m/z, intensity, retention time, compound IDs) from experiments or external sources, and need to prepare it for ingestion into the EISA-EXPOSOME R Shiny platform for suspect screening.
    0 installs
92. ▌
    Spectral Intensity Trace Extraction · holobiomicslab

    Use when you have a Thermo Fisher Orbitrap .raw file and need to recover the intensity profile of a specific m/z value or peptide across the LC separation dimension (chromatogram), particularly when calibrating retention times against internal standards (iRT peptides), performing quality control.
    0 installs
93. ▌
    Spectral Quality Metrics Extraction · holobiomicslab

    Use when you have multi-sample MS1 data (from Agilent, Thermo, Bruker, or mzML formats) and need to quantify ion-level quality attributes—such as signal consistency, noise characteristics, or chromatographic stability—to either flag outlier samples or validate data fitness for downstream.
    0 installs
94. ▌
    Streamlit Session State Integration · holobiomicslab

    Use when when building a Streamlit web application that must coordinate stateful workflow execution across multiple reruns triggered by user interactions (e.
    0 installs
95. ▌
    Structured Data Matrix Construction · holobiomicslab

    Use when you have raw LipidSearch or LIQUID output files (CSV or TSV format) containing lipid identifiers and quantification columns (relative intensity or area values), and need to construct a clean, analyzable data matrix with consistent lipid nomenclature and no missing values in critical fields.
    2 installs
96. ▌
    Tensorflow Serving Layer Inspection · holobiomicslab

    Use when after deploying a TensorFlow model via TensorFlow Serving (e.
    0 installs
97. ▌
    Test Suite Execution And Validation · holobiomicslab

    Use when when you have cloned or obtained a Python package repository and need to verify that the package can be installed from source and that its test suite passes without errors.
    0 installs
98. ▌
    Unknown Sample Reference Comparison · holobiomicslab

    Use when you have a preprocessed unknown sample spectrum (m/z peaks and intensities) from high-throughput mass spectrometry (DI-MS, ASAP-MS, or ambient ionization methods) and need to identify the species or authenticate a sample against a curated reference database of known spectra.
    0 installs
99. ▌
    Web API Service Integration Mapping · holobiomicslab

    Use when you need to support multiple external services (CIR, CTS, PubChem, IDSM, BridgeDb, RDKit) for chemical identifier conversions (.
    0 installs
100. ▌
     Within Subject Correlation Modeling · holobiomicslab

     Use when your metabolomics dataset is in long format with repeated measurements per subject (id), a grouping variable (e.g., disease status or treatment arm), and metabolite abundances measured across time or visits.
     0 installs