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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Galaxy Tool Wrapper Development · holobiomicslab

   Use when you have a working R package that performs established preprocessing, analysis, or statistical workflows on formatted tabular data (e.
   0 installs
2. ▌
   Gam Model Diagnostic Evaluation · holobiomicslab

   Use when after fitting candidate GAM splines with B-spline basis functions across a range of basis dimensions (k values 12–20) to anchor feature pairs (m/z and retention time coordinates).
   0 installs
3. ▌
   Ground Truth Ordinal Validation · holobiomicslab

   Use when after running retention-order prediction on a test or evaluation dataset, when you have both predicted retention orderings (from RankSVM, SVR, or similar ordinal regressors) and experimentally validated ground-truth retention orders from the same chromatographic system(s).
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4. ▌
   HTTP File Upload Implementation · holobiomicslab

   Use when you are building the initial data ingestion step of a high-throughput MS platform and need to accept raw MS files from users or instruments via a web interface. Use this skill when you require automated validation of vendor-specific formats (Thermo .
   0 installs
5. ▌
   Imzml Continuous Format Parsing · holobiomicslab

   Use when you have acquired raw mass spectrometry imaging data in imzML continuous format (e.g., from CardinalIO or other MSI instruments) and need to load it into R as a structured MSImagingExperiment object to perform statistical analysis, normalization, or visualization.
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6. ▌
   Intensity Normalization Spectra · holobiomicslab

   Use when after noise reduction when working with imported imzML MSI data where pixel-to-pixel or sample-to-sample intensity variations due to instrumental sensitivity or sample loading differences must be corrected before mean intensity calculation, ROI analysis, or metabolite annotation.
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7. ▌
   Internal Standard Normalization · holobiomicslab

   Use when your metabolomics dataset includes internal standard metabolites (marked in the metabolitedata IS column), log-transformed featuredata are available, and you need to remove systematic variation attributable to instrument drift, sample matrix effects, or batch differences while preserving.
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8. ▌
   JSON Table To Matrix Conversion · holobiomicslab

   Use when you have extracted tabular data (e.g., from experimental spreadsheets) in intermediate JSON form with a single table of records, and you need to produce a list of dictionaries (array of objects) for deposition into a data repository such as the Metabolomics Workbench, or when you need to.
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9. ▌
   Kegg Data Retrieval And Parsing · holobiomicslab

   Use when when you have selected one or more organisms to analyze and need to extract their complete metabolic reaction and metabolite data from KEGG in order to build a network representation.
   0 installs
10. ▌
    La Icp Ms Isotope Normalization · holobiomicslab

    Use when you have multi-isotope LA-ICP-MS data (e.
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11. ▌
    Lc Hrms 2d Area Standardization · holobiomicslab

    Use when after detecting local-maxima in LC-HRMS profile mode datasets and before training or inference with a CNN model for peak classification.
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12. ▌
    Linear Regression Model Fitting · holobiomicslab

    Use when when you have a targeted metabolomics dataset with known concentration values for calibration ('curve') and quality control ('qc') samples, peak area intensities for those samples, and you need to establish and validate a concentration-prediction model before applying it to unknown samples.
    0 installs
13. ▌
    Marr Output Object Manipulation · holobiomicslab

    Use when when you have a Marr() output object containing reproducibility statistics computed across replicate experiments and need to reduce dimensionality by retaining only features or sample pairs that meet reproducibility criteria (percentage of reproducible signals exceeding feature-level.
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14. ▌
    Mass Difference Adduct Matching · holobiomicslab

    Use when after correlation-based feature pairing has identified feature groups with matching temporal intensity profiles through direct-injection or plasma ionization mass spectrometry experiments. You have a set of putative feature-pair candidates and need to assign specific chemical identities (e.
    0 installs
15. ▌
    Mass Spectrometry Preprocessing · holobiomicslab

    Use when when you have raw mass-spectrometry data (precursor m/z, ionization mode, and fragment m/z–intensity pairs) that must be fed into a CNN model for metabolite annotation via compound fingerprint prediction.
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16. ▌
    Mass To Charge Ratio Validation · holobiomicslab

    Use when after loading MS-Dial feature tables (e.g., Urine_RP_NEG_norm.txt or Urine_RP_POS_norm.txt) and before sample-level filtering or imputation, whenever the feature abundance matrix contains m/z values acquired across multiple chromatographic runs or polarities.
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17. ▌
    Mass Tolerance Window Filtering · holobiomicslab

    Use when after calculating neutral mass from observed m/z and adduct type, and before ranking candidates by chemical plausibility. Use it whenever querying a formula database (KEGG, PubChem, or custom) to retrieve all molecular formulae within a specified mass tolerance window of each neutral mass.
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18. ▌
    Matlab Workspace Initialization · holobiomicslab

    Use when when you have mass spectrometry imaging root datasets paired with accompanying .mat workspace files (as in the B73 and Oaxacan Green genotypes from Sama et al.
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19. ▌
    Matplotlib Figure Customization · holobiomicslab

    Use when when rendering spectrum data (m/z vs. intensity arrays) from MZA files and need to control visual presentation: applying m/z range windows, setting line colors and labels for legend identification, sizing the figure, or choosing between interactive display versus file export.
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20. ▌
    Metabolic Marker Identification · holobiomicslab

    Use when after batch effect removal and sample integration, when you have a normalized feature-by-sample abundance matrix (finalData) with corresponding sample group labels (finalLabel), and need to identify which metabolites discriminate between biological conditions or phenotypes for focused.
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21. ▌
    Metabolite Database Integration · holobiomicslab

    Use when you need to construct a reference metabolomics database from scratch or when existing public databases (HMDB, MassBank, METLIN) need to be merged into a single queryable resource for metabolite annotation in untargeted mass spectrometry analysis.
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22. ▌
    Metabolite Feature M Z Matching · holobiomicslab

    Use when you have (1) a benchmark dataset of known molecules with accurate m/z values, retention time boundaries, and isotopologue identifiers for all enviPat-predicted adducts;
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23. ▌
    Metabolite Feature Organization · holobiomicslab

    Use when you have raw imzML and ibd (ion binary data) files from spatial mass spectrometry imaging and need to convert them into a standardized AnnData representation where m/z values are features (columns), spatial spots are observations (rows), and intensities form the feature matrix.
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24. ▌
    Metabolite Network Construction · holobiomicslab

    Use when when you have a list of input metabolites (e.g., from differential metabolomics analysis) and need to: (1) contextualize them within known metabolic pathways; (2) assess their structural importance in the pathway network rather than statistical significance alone;
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25. ▌
    Tensorflow Model Layer Inspection · holobiomicslab

    Use when after converting or downloading a pre-trained Keras model to HDF5 TensorFlow 2.3.0 format, particularly when integrating the model into a fixed-interface pipeline (e.g., NP Classifier) that expects specific named input/output layers.
    0 installs
26. ▌
    Test Result Parsing And Reporting · holobiomicslab

    Use when when you need to validate that a package's periodic integration test suite (distinct from unit tests) passes as expected, or when you must collect and communicate structured evidence of test outcomes across multiple test cases.
    0 installs
27. ▌
    U13c Labeled Lipid Identification · holobiomicslab

    Use when you have measured CCS values from (LC-)IM-MS samples spiked with U¹³C labeled internal standards (e.
    0 installs
28. ▌
    Unit Testing Conditional Branches · holobiomicslab

    Use when when implementing or refactoring a FileInterface._open method or similar polymorphic dispatcher that conditionally instantiates different handler classes based on file extension (e.g., .gz, .db) or format metadata (e.g., indexed gzip detection).
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29. ▌
    Validated Link Ranking Comparison · holobiomicslab

    Use when when you have computed multiple independent scoring functions (e.
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30. ▌
    Vectorized Operation Verification · holobiomicslab

    Use when when implementing or auditing S4 replacement methods (e.
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31. ▌
    Web Service Deployment Validation · holobiomicslab

    Use when when you need to confirm that a publicly hosted academic web service (such as molDiscovery) is live and responding at a documented endpoint URL, or when troubleshooting access issues reported by end users.
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32. ▌
    Abstract Syntax Tree Construction · holobiomicslab

    Use when you have a tokenized sequence of domain-specific language tokens and need to construct a hierarchical, unambiguous representation that can be validated against language design principles (expressiveness, precision, scalability, readability) and passed to downstream execution engines.
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33. ▌
    Asynchronous Method Introspection · holobiomicslab

    Use when you have a plugin-based converter architecture (e.g., web services and compute libraries in separate directories) and you need to automatically discover all available (source_attribute, target_attribute, converter_name) conversion triples without hardcoding them.
    0 installs
34. ▌
    Basepeak Intensity Identification · holobiomicslab

    Use when when you have Thermo Fisher Scientific .raw files from an Orbitrap instrument and need to identify the m/z value and corresponding intensity of the most abundant ion in each MS1 scan for quality control, method optimization, or feature extraction in a modular R-based proteomics pipeline.
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35. ▌
    Biosynformatic Vector Computation · holobiomicslab

    Use when you have a natural product molecule structure in SMILES, InChI, or SDF format and need to convert it into a fixed-length numerical vector representation (fingerprint) that preserves biosynthetic and chemical information for machine learning, similarity searching, or class prediction tasks.
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36. ▌
    Candidate Psm Cardinality Control · holobiomicslab

    Use when when rescoring PSMs from a search engine with MS²Rescore and you need to (1) constrain computational cost by reducing the number of candidates fed to feature generators and rescoring engines, (2) control false discovery rate correctly by removing lower-ranking PSMs before final statistical.
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37. ▌
    Comparative Performance Profiling · holobiomicslab

    Use when when you have implemented a new or optimized mass spectrometry data processing library and need to demonstrate its computational advantage over established alternatives (e.g., pymzML, pyOpenMS) on real proteomics data. Trigger on availability of: (1) a common input dataset (e.
    0 installs
38. ▌
    Conda Environment File Generation · holobiomicslab

    Use when when you have identified all software dependencies and their exact pinned versions from project documentation (README, setup files, or supplementary materials) and need to create portable environment specifications for a scientific implementation.
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39. ▌
    Conda Environment Reproducibility · holobiomicslab

    Use when you have received a conda/pip requirements file (e.g., jestr_requirements.txt) and need to run code that was trained and tested on a specific GPU setup (e.g., NVIDIA A100 with CUDA 11.8).
    0 installs
40. ▌
    Configuration File Interpretation · holobiomicslab

    Use when when you have PSM files from proteomics search engines (MaxQuant, MSGFPlus, Sage, etc.) that use non-standard modification notation (e.g., 'ox', '+57.02146', or mass-shift labels) and need to resccore peptide identifications with MS²Rescore.
    0 installs
41. ▌
    Conformer Ensemble Energy Ranking · holobiomicslab

    Use when after RDKit has generated a large set of 3D conformers for a molecule in SDF or XYZ format, and before submitting conformers to computationally expensive quantum-chemical methods (e.g., QUICK).
    0 installs
42. ▌
    Consensus Clustering Optimization · holobiomicslab

    Use when when you have a feature attribution matrix (e.g., microbe-metabolite interaction scores) from ensemble neural network training and need to group rows and columns into functionally coherent modules without pre-specifying cluster numbers.
    0 installs
43. ▌
    Constraint Based Model Validation · holobiomicslab

    Use when after gap-filling metabolic models in a community context when you need to verify that filled reactions maintain stoichiometric balance, that biomass production is feasible under community-level constraints, and that cross-member metabolic dependencies are satisfied.
    0 installs
44. ▌
    Count Matrix Statistical Modeling · holobiomicslab

    Use when after count matrix preprocessing (normalization, batch correction, low-count filtering) when you have a feature-by-sample count matrix and phenotype metadata, and you need to identify differentially expressed genes, miRNAs, isoforms, or other features across treatment groups or conditions.
    0 installs
45. ▌
    Cross Domain Metadata Integration · holobiomicslab

    Use when when you have conducted batch MS/MS searches across one or more domain-specific MASST tools and need to combine their hit scores, metadata annotations, and taxonomic lineages into a single coherent result set for comparative analysis or publication.
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46. ▌
    Cross Organism Network Comparison · holobiomicslab

    Use when you have selected two organisms whose metabolic networks are available in KEGG and you need to quantitatively assess their structural and functional similarity to identify shared or divergent metabolic capabilities for comparative systems biology, drug target discovery, or evolutionary.
    0 installs
47. ▌
    Cross Validation Parameter Tuning · holobiomicslab

    Use when when building Cox-PH or Cox-nnet survival models from expression or metabolomic feature matrices paired with event/time vectors, and you need to select optimal regularization strength (alpha), cross-validation fold count (nfold), risk stratification method, and optimization strategy before.
    0 installs
48. ▌
    Data Type Constraint Verification · holobiomicslab

    Use when when ingesting or updating MassBank records in plain-text or structured format, and you need to verify that metadata fields (accession, name, formula, mass, spectrum peaks) comply with type definitions, presence requirements, and allowed value ranges.
    0 installs
49. ▌
    Deep Learning Survival Prediction · holobiomicslab

    Use when you have metabolomic or expression feature data, sample-level event indicators (e.
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50. ▌
    Deployment Artifact Documentation · holobiomicslab

    Use when preparing a scientific application (such as a metabolite annotation tool) for deployment to a shared or production app server, particularly when the deployment requires external database access, Java library dependencies, and credential management.
    0 installs
51. ▌
    Dereplication Candidate Filtering · holobiomicslab

    Use when after spectral database dereplication (using Spectra) and compound database dereplication (using SIRIUS or MetFrag) have produced candidate annotations in CSV or JSON format.
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52. ▌
    Dgl Molecular Graph Featurization · holobiomicslab

    Use when you have a set of SMILES or molecular structures and need to represent them as graph tensors for a Graphormer or other graph neural network model that predicts molecular properties (e.g., retention time, spectroscopic features).
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53. ▌
    Docker Volume Mount Configuration · holobiomicslab

    Use when deploying the ipbhalle/metfragweb container and you need to supply custom MetFrag settings (ChemSpider tokens, proxy servers, local database connections) without modifying the container image.
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54. ▌
    Executable Version String Parsing · holobiomicslab

    Use when your R package wraps a compiled .NET assembly or binary executable and you need to expose the version of that dependency to users at runtime for troubleshooting, validation, or documentation purposes.
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55. ▌
    Fatty Acid Composition Generation · holobiomicslab

    Use when you need to systematically enumerate all possible lipid species within a defined analytical scope—specifically when you have specified one or more lipid classes (e.g., phosphatidylcholine, triacylglycerol) and fatty acid composition ranges (e.
    0 installs
56. ▌
    Feature Table Comparison Analysis · holobiomicslab

    Use when after running Paramounter's peak-height optimization on XCMS CentWave–extracted metabolomic features when you need to decide whether to accept the optimized threshold (maximizing true positives) or apply a higher threshold to reduce false positives and software crashes.
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57. ▌
    Feedforward Network Configuration · holobiomicslab

    Use when when implementing multiple spectrum predictor baseline models (NEIMS, MassFormer, etc.) and you need to isolate the impact of encoder architecture on predictive performance.
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58. ▌
    File Format Conversion Validation · holobiomicslab

    Use when when you have raw mzML or mzXML mass spectrometry data files that need to be archived or transmitted with minimal storage footprint, and you must verify that the decompressed output exactly reproduces the original input at the byte level.
    0 installs
59. ▌
    File Format Detection And Routing · holobiomicslab

    Use when when you receive a mass spectrometry imaging dataset in unknown or mixed vendor formats and need to apply format-specific preprocessing before generating ion images.
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60. ▌
    File Format Validation Proteomics · holobiomicslab

    Use when when raw MS files are uploaded to MSConnect via the Raw File Uploader and must be verified for compatibility with downstream processing tools (e.g., Proteomics_Data_Processor) before routing to the processing queue.
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61. ▌
    File Io Error Handling Robustness · holobiomicslab

    Use when when designing or integrating a file parser for mass spectrometry formats (.raw Thermo RAW format, .mzml XML-based format) in a metabolomics processing pipeline, or when reading legacy or heterogeneous instrument output where file integrity cannot be guaranteed.
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62. ▌
    Filter Module Toggle Verification · holobiomicslab

    Use when you need to confirm that a software API or tool correctly implements a boolean control over an optional filter module, particularly in contexts where filter activation state directly affects the set of predicted metabolites.
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63. ▌
    Filter Threshold Parameterization · holobiomicslab

    Use when when expanding a compound set through multi-generation Pickaxe runs, use this skill if you want to retain compounds based on a similarity or property metric (e.
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64. ▌
    Fold Change Frequency Aggregation · holobiomicslab

    Use when after performing univariate statistical testing (t-test or ANOVA via omu_summary or omu_anova) on metabolomics count data, use this skill when you need to summarize how many metabolites in each class showed significant increase or decrease (padj ≤ 0.05).
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65. ▌
    Galaxy Installation Configuration · holobiomicslab

    Use when you have a Galaxy Master branch installation (or specific commit c429777c93680dcee449fe410f5360afbe673758) and need to add metabolomics tools from Galaxy-M.
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66. ▌
    Galaxy Tool XML Option Formatting · holobiomicslab

    Use when when integrating a multi-backend metadata enrichment package (like MSMetaEnhancer) into Galaxy, and you need to expose all supported conversion options—such as SMILES, InChI, or CAS number conversions across multiple web services (CIR, CTS, PubChem, IDSM, BridgeDb) and compute backends.
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67. ▌
    Gallery Benchmark Data Extraction · holobiomicslab

    Use when you have access to a computation-times table or performance log documenting rendering execution times for multiple visualization examples across different plotting backends (e.
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68. ▌
    Gpu Accelerated Similarity Search · holobiomicslab

    Use when you have a large spectral library and many query spectra to search against it, and you need to identify both unmodified and open-modification peptides with strict false discovery rate control.
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69. ▌
    Graph Representation Construction · holobiomicslab

    Use when you have KEGG metabolic data for one or more organisms and need to simultaneously analyze network topology and functional pathway organization—for example, when comparing metabolic capabilities between species for drug target discovery or when you need to expose both structural rewiring.
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70. ▌
    Group Stratified Curve Generation · holobiomicslab

    Use when you have omics data with group labels (e.g., treatment vs. control, disease vs. healthy) and need to visualize how the cumulative distribution of a continuous variable (e.g., gene expression, abundance) differs between groups.
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71. ▌
    Hash Based Deduplication Workflow · holobiomicslab

    Use when when processing open mass spectrometry library (OMSL) data that may contain duplicate spectral records (e.
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72. ▌
    Hdf5 Cardinal Format Preservation · holobiomicslab

    Use when after performing isotopic correction, quantitation, or other pixel-level transformations on a feature-by-pixel intensity matrix imported from an imzML file via Cardinal's HDF5 layout.
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73. ▌
    Hdf5 File Structure Specification · holobiomicslab

    Use when when exporting quantified MSI data (feature-by-pixel intensity matrices with associated ion m/z, lipid annotations, and pixel spatial coordinates) from LipidQMap and you need to produce a standards-compliant HDF5 container that can be read by Cardinal and other MSI analysis tools.
    0 installs
74. ▌
    Histogram Bin Width Configuration · holobiomicslab

    Use when you have uploaded a numeric column (e.g., H/C ratio, O/C ratio, or other derived properties from high-resolution mass spectrometry) and you are generating a histogram in Punc'data's Canvas tab.
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75. ▌
    Identifier Mapping Implementation · holobiomicslab

    Use when when you have lipid names or abbreviations sourced from multiple databases (HMDB, LIPID MAPS, LipidHome, RefMet, SwissLipids) or software tools (LipidSearch, MS-DIAL, MZmine2, LipidBlast, etc.) and need to normalize them into a single canonical representation to enable data integration.
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76. ▌
    Inchikey Identifier Normalization · holobiomicslab

    Use when gNPS has stopped supplying ClassyFire ontology information for spectral library matches (as of the ConCISE documentation snapshot) and you need to manually retrieve chemical classifications.
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77. ▌
    Ion Formula Matrix Classification · holobiomicslab

    Use when you have peak data from MSI experiments (stored as .zip peak matrix files) where matrix ions (e.g., silver adducts in AgLDI-MSI) dominate the spectrum and obscure analyte signals.
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78. ▌
    Ion Mobility Class Stratification · holobiomicslab

    Use when you have TWIM-MS experimental data with assigned biomolecular class labels (e.g., peptides, lipids, carbohydrates) and arrival time measurements, and you need to compute CCS values conditioned on class membership.
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79. ▌
    JSON Structured Report Generation · holobiomicslab

    Use when after Mass2Motif annotation candidates have been ranked and filtered by similarity score (using Spec2Vec embeddings queried against MotifDB), you need to serialize the ranked results into a standardized, hierarchical format that preserves confidence metadata and enables programmatic access.
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80. ▌
    Knn Imputation Quality Assessment · holobiomicslab

    Use when after deciding to use KNN imputation on a metabolomic assay matrix with missing values, but before proceeding to normalization and statistical testing. Trigger conditions include: (1) your metabolomic dataset contains metabolites with varying degrees of missingness across samples;
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81. ▌
    Large Scale Database Construction · holobiomicslab

    Use when you have a collection of molecular structures (as SMILES or SDF files) and need to generate pre-computed CCS values for fast retrieval in downstream mass spectrometry workflows.
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82. ▌
    Lipid Concentration Normalization · holobiomicslab

    Use when your lipidomics experiment includes spiked internal lipid standards with known absolute concentrations, and you have a data matrix of signal intensities (samples × lipids) from LipidSearch or LIQUID output.
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83. ▌
    Lipid Feature Identifier Matching · holobiomicslab

    Use when you have an isotope-corrected or raw MSI dataset stored in HDF5 format following Cardinal::HDF5 conventions, a user-provided internal standard definition (sample identifier and/or feature name), and need to locate and extract the intensity row for that lipid before performing ratio-based.
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84. ▌
    Lipid Metadata Annotation Mapping · holobiomicslab

    Use when when exporting in-memory generated spectra as MSP-format spectral libraries, you must first map each spectrum record to required MSP fields (NAME, PRECURSORMZ, SPECTRUM) and optional metadata annotations.
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85. ▌
    Lipid Nomenclature Simplification · holobiomicslab

    Use when you have spatial metabolomics data with semicolon-delimited isomer name annotations (such as the 'all_IsomerNames' column in SpaMTP Seurat objects) and you need to reduce annotation complexity before pathway analysis, statistical testing, or visualization.
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86. ▌
    Mass Spectrometry File Conversion · holobiomicslab

    Use when you have vendor raw mass spectrometry data files (.raw) from a commercial instrument and need to convert them to open formats (mzML for spectral data, imzML for imaging mass spectrometry) for compatibility with third-party analysis software or to meet open-data standards.
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87. ▌
    Mass Spectrometry Peak Validation · holobiomicslab

    Use when after peak alignment across all spectra in an MSImagingExperiment using peakAlign(), when you need to reduce the feature set to high-confidence peaks by removing spurious or low-frequency detections.
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88. ▌
    Mass Trace Separation By Grouping · holobiomicslab

    Use when your pandas DataFrame contains mass spectrometry data with retention time (rt) and intensity columns AND a column representing different mass-to-charge (m/z) values or ion identifiers. This is particularly relevant when generating chromatogram plots from data with multiple mass traces (e.
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89. ▌
    Metabolic Function Classification · holobiomicslab

    Use when when you have reconstructed metabolic networks from two or more organisms in KEGG and need to compare them not only in terms of reaction topology but also in terms of which metabolic functions (e.g., glycolysis, citric acid cycle) are present and how they differ.
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90. ▌
    Metabolite Class Subset Filtering · holobiomicslab

    Use when when you have an omu_summary output dataframe with Class metadata and adjusted p-values (padj), and you need to focus downstream analysis (e.
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91. ▌
    Metabolomics Data Matrix Handling · holobiomicslab

    Use when when you have raw metabolomics peak intensities or concentrations and accompanying sample metadata (batch, run order, sample type, factors of interest) and need to organize them into the featuredata, sampledata, and metabolitedata dataframes that NormalizeMets functions expect.
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92. ▌
    Metabolomics Data Quality Control · holobiomicslab

    Use when after loading raw metabolomics data (e.g., from Metabolon, Nightingale, Olink, or SomaLogic platforms) into a Metaboprep object and before statistical analysis or modeling.
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93. ▌
    Metabolomics Parameter Extraction · holobiomicslab

    Use when you have raw untargeted metabolomics data in mzML, mzXML, or CDF format from qTOF, Orbitrap, or FTICR mass analyzers, at least 3 samples, a sample metadata spreadsheet linking filenames to experimental factors, and need to generate optimized processing parameters for XCMS or MZmine2.
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94. ▌
    Missing Data Mechanism Assessment · holobiomicslab

    Use when when you have a filtered metabolite abundance matrix with remaining missing values after feature-level filtering (e.g., removal of metabolites with >80% missingness), and you need to decide whether missingness is concentrated in specific features or sample pairs, or distributed randomly.
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95. ▌
    Missing Value Imputation Strategy · holobiomicslab

    Use when your feature intensity table (samples × compounds) contains NA values and you intend to apply log transformation or scaling-based normalization. Specifically, apply this skill when the transf_data function is invoked with missing_replace=TRUE, before any log transformation or scaling step.
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96. ▌
    Model Generalizability Evaluation · holobiomicslab

    Use when you have a pre-trained or newly retrained graph neural network for collision cross section prediction and need to measure whether its performance generalizes across different molecular datasets (e.g., training on METLIN but evaluating on CCSBase).
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97. ▌
    Molecular Conformer Preprocessing · holobiomicslab

    Use when you have a set of molecular SMILES strings and need to prepare them as inputs to a deep-learning CCS prediction model.
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98. ▌
    Molecular Fingerprint Calculation · holobiomicslab

    Use when you have a collection of small molecules in standardized format (SMILES or SDF) that require quantitative chemical feature representation for machine learning or comparative analysis.
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99. ▌
    Molecular Representation Learning · holobiomicslab

    Use when when you have a collection of molecules with known property labels (e.g., retention times on a chromatographic column) and need to predict those properties on new compounds.
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100. ▌
     Molecular Structure Parsing Rdkit · holobiomicslab

     Use when you have raw molecular structures in SMILES or SDF format from a chemical database (e.
     0 installs