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HolobiomicsLab

@holobiomicslab source repo

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1. ▌
   Physicochemical Descriptor Extraction · holobiomicslab

   Use when when you have validated RDKit molecule objects derived from PubChem or HMDB molecule IDs and need to generate quantitative chemical property representations as one modality in a multimodal feature tensor for neural network training.
   0 installs
2. ▌
   Pytorch Installation And Verification · holobiomicslab

   Use when when setting up a computational environment to run pre-trained PyTorch models that were trained on GPU hardware (e.g., NVIDIA A100 with CUDA 11.8), and the released model weights are GPU-trained artifacts. Specifically, when you have a jestr_requirements.
   0 installs
3. ▌
   Quality Control Metric Interpretation · holobiomicslab

   Use when after normalizing a metabolomics featuredata matrix (samples × metabolites), use this skill to visually and quantitatively assess normalization quality. Specifically, apply it when you need to decide whether a chosen normalization method (e.
   0 installs
4. ▌
   Query String Parsing And Tokenization · holobiomicslab

   Use when when you have a user-provided or system-generated query string containing a chemical structure in unknown or mixed format, and you need to route it to a structure-specific API endpoint (such as ClassyFire) that requires knowing whether the input is SMILES, InChI, IUPAC nomenclature, or.
   0 installs
5. ▌
   Rapid Spectrum Retrieval Optimization · holobiomicslab

   Use when you have a large collection of mass spectrometry spectra (m/z and intensity pairs) and need to rapidly retrieve similar or candidate spectra from the archive in response to queries.
   0 installs
6. ▌
   Recursive Descent Parser Construction · holobiomicslab

   Use when you have a formal grammar specification for a domain-specific language (or can extract one from reference implementations) and need to convert user-written query strings into structured, machine-processable representations (ASTs or JSON) that preserve domain-specific semantics—such as mass.
   0 installs
7. ▌
   Reference Peak Matching And Alignment · holobiomicslab

   Use when when you have a processed mass spectrum object (e.g., from Bruker FT-ICR acquisition) and a reference peak list (e.g., SRFA.
   0 installs
8. ▌
   Release Versioning Schema Enforcement · holobiomicslab

   Use when when preparing a release branch for a Maven-based project (like NMRFx) and you need to verify that all pom.xml files in the repository tree declare identical version strings before applying release branch naming conventions (e.g., 'release/X.Y.Z').
   0 installs
9. ▌
   S7 Object Construction And Validation · holobiomicslab

   Use when after successfully parsing vendor-specific metabolomic data files (Metabolon Excel, Nightingale, Olink, SomaLogic) into separate data, samples, and features tables, and before applying quality control or batch normalization pipelines.
   0 installs
10. ▌
    Smiles Inchi Fasta Format Recognition · holobiomicslab

    Use when when you have a mixed batch of chemical structure queries in unknown or variable formats (e.
    0 installs
11. ▌
    Soft Thresholding Adjacency Weighting · holobiomicslab

    Use when after computing a biweight midcorrelation similarity matrix across normalized metabolite abundance data, and before hierarchical clustering on dissimilarity.
    0 installs
12. ▌
    Spatial Distribution Pattern Analysis · holobiomicslab

    Use when when you have loaded MSI peak data with associated m/z values and need to disambiguate matrix ions from analyte ions. Apply this skill when chemical formula alone is insufficient (e.g., overlapping or isobaric peaks exist) and you have pixel-level spatial intensity maps for each ion.
    0 installs
13. ▌
    Spectral Fragment Identifier Matching · holobiomicslab

    Use when when you have downloaded fragment records from separate experimental and predicted online databases and need to verify that each fragment can be traced back to a valid compound entry in a reference compound database (e.g., SDF-format DNA adduct compound collection).
    0 installs
14. ▌
    Spectral Noise Filtering Dynamic Peak · holobiomicslab

    Use when use this skill after normalizing, smoothing, and baseline-reducing MSImagingArrays objects when you need to detect peaks across multiple spectra with consistent SNR-based thresholding.
    0 installs
15. ▌
    Spectral Peak Alignment Across Pixels · holobiomicslab

    Use when after peak picking across individual spectra in an MSImagingExperiment, when you need to harmonize peak m/z positions across pixels to account for small shifts in peak location due to instrumental drift, calibration differences, or natural variation.
    0 installs
16. ▌
    Spectral Peak Detection And Alignment · holobiomicslab

    Use when after noise filtering and baseline correction have been applied to mass spectrometry data (DI-MS, ASAP-MS, LDI-MS, or other high-throughput MS formats in mzML, mzXML, or vendor formats).
    0 installs
17. ▌
    Spectral Reference Peak Summarization · holobiomicslab

    Use when after peak picking and alignment have been performed on preprocessed spectra (normalized, smoothed, and baseline-reduced), and you need to create a unified peak reference table that can be applied consistently across all spectra in an imaging dataset.
    0 installs
18. ▌
    Statistical Result Mapping To Display · holobiomicslab

    Use when you have omics abundance or expression measurements paired with corresponding statistical results (p-values, effect sizes, fold-changes) and need to create an interactive, exploratory display where each omics feature (protein, metabolite, gene) occupies its own panel and can be filtered or.
    0 installs
19. ▌
    Structure Organism Pair Deduplication · holobiomicslab

    Use when you have a curated natural products dataset (e.g., LOTUS platinum validation dataset in TSV format) and need to establish ground-truth counts of unique chemical structures, unique organisms, and unique referenced structure-organism associations.
    0 installs
20. ▌
    System Path Environment Configuration · holobiomicslab

    Use when when setting up imzML Writer for the first time on a new machine, or when raw vendor mass spectrometry file conversion fails with 'msconvert not found' or Docker image unavailable errors. Specifically: on Windows/PC systems before invoking RAW_to_mzML conversion;
    0 installs
21. ▌
    Systems Biology Model Standardization · holobiomicslab

    Use when you have multiple draft metabolic reconstructions of community members or assembly variants (e.g., from different annotation pipelines or genome assemblies) in diverse or non-standard formats, and you need to merge them into a single consensus model.
    0 installs
22. ▌
    Targeted Compound Metadata Formatting · holobiomicslab

    Use when you have a raw list of target compounds (in .xlsx, CSV, or database form) with heterogeneous column names and layouts, and you need to prepare it for targeted peak detection, EIC extraction, or quality metric calculation in TARDIS or similar LC–MS metabolomics tools.
    0 installs
23. ▌
    Theoretical To Observed Peak Matching · holobiomicslab

    Use when you have a mass spectrum scan containing observed precursor ions (m/z, intensity pairs) in a narrow isolation window, a known peptide sequence with specified charge state and stable isotope labeling parameters (atom type, incorporation probability), and you need to determine which observed.
    0 installs
24. ▌
    Time Temperature Degradation Modeling · holobiomicslab

    Use when you are planning a blood sampling campaign and need to know whether specific lipid or polar-metabolite analytes will degrade during storage or processing delays at known temperatures, or you are troubleshooting retrospective stability concerns for analytes already measured under documented.
    0 installs
25. ▌
    Trend Classification From Fold Change · holobiomicslab

    Use when when you have harmonized metabolomics data with fold-change and p-value columns from multiple studies and need to assign trend categories prior to vote-counting meta-analysis.
    0 installs
26. ▌
    Statistics Biomarker Discovery Workflow · holobiomicslab bundle

    Use when you have a metabolomics feature/quant table and want a statistically rigorous comparison and candidate biomarkers — cleaning and normalization, multivariate analysis, differential features, enrichment/pathway analysis, and biomarker selection with ROC.
    0 installs
27. ▌
    Adjacency Matrix Sparsity Analysis · holobiomicslab

    Use when immediately after calling squidpy.gr.spatial_neighbors() or similar spatial graph construction methods on an AnnData object. It is essential when validating that the computed spatial graph has been correctly stored in adata.
    0 installs
28. ▌
    Alternative Splicing Event Parsing · holobiomicslab

    Use when when you have a GTF genome annotation and need to identify all local alternative splicing events (SE, RI, A5/A3, MX, AF/AL) or transcript-level isoform events for a given gene set, prior to quantifying PSI values across samples or performing differential splicing analysis.
    0 installs
29. ▌
    Gene Expression Log Transformation · holobiomicslab

    Use when after normalizing total UMI counts per cell using normalize_total, and before PCA or feature selection. Use this when working with raw or depth-normalized count matrices where gene expression values span multiple orders of magnitude and variance is not homogeneous across expression levels.
    0 installs
30. ▌
    Gene Filtering By Expression Level · holobiomicslab

    Use when you have a large gene expression matrix (e.g., thousands of genes) from normalized microarray or RNA-seq data and need to reduce computational burden before running pathway enrichment analysis (e.g., GSEA or GESECA).
    0 installs
31. ▌
    Independent Filtering Optimization · holobiomicslab

    Use when you have completed DESeq differential expression analysis on a DESeqDataSet and obtained raw results with p-values across all genes.
    0 installs
32. ▌
    Microarray Expression Data Loading · holobiomicslab

    Use when you have raw or normalized microarray expression matrices stored in public repositories (GEO accessions) along with sample metadata, and you need to load both into R as structured objects (expression matrix and phenotype data frame) to construct a design matrix and fit linear models for.
    0 installs
33. ▌
    Python Data Structure Verification · holobiomicslab

    Use when after executing a spatial analysis function (e.g., squidpy.gr.sepal) that modifies or augments a data object, verify that the expected output fields exist with correct names, data types, and array dimensions before proceeding to interpretation or visualization.
    0 installs
34. ▌
    Trajectory Inference Preprocessing · holobiomicslab

    Use when you have raw or normalized single-cell RNA-seq expression data stored in an AnnData object (`.h5ad` format) and your analysis goal is to infer developmental or differentiation trajectories.
    0 installs
35. ▌
    Transcript Level Count Aggregation · holobiomicslab

    Use when you have transcript-level abundance and count estimates from salmon, sailfish, kallisto, or oarfish and need gene-level matrices for downstream differential analysis with edgeR, DESeq2, or limma-voom.
    0 installs
36. ▌
    Candidate Spectrum Retrieval And Ranking · holobiomicslab

    Use when when you have a large reference MS/MS spectral library (>10k spectra) and need to perform open modification searches on query spectra without exhaustively comparing against every library entry.
    0 installs
37. ▌
    Mass Spectrometry File Format Conversion · holobiomicslab

    Use when you have raw MS data files in vendor-native format (.raw, .d, .ms) from CE-MS or LC-MS instruments and need to process them through AriumMS or other open-source metabolomics pipelines that require standardized XML-based interchange formats.
    0 installs
38. ▌
    Metabolite Detection Matrix Construction · holobiomicslab

    Use when after GNPS spectral library matching has been completed on a batch of MS2 spectra from public MassIVE datasets and you need to aggregate chemical annotations into a tabular format suitable for downstream comparative metabolomics, co-analysis, or chemical explorer visualizations across.
    0 installs
39. ▌
    Spectral Clustering And Feature Grouping · holobiomicslab

    Use when you have raw MS/MS feature data with m/z, retention time, and fragmentation spectra from an untargeted metabolomics experiment, and you need to annotate reaction-derived metabolites of xenobiotics without relying on a priori targeted methods.
    0 installs
40. ▌
    Compound Area Aggregation Across Samples · holobiomicslab

    Use when you have a GC-MS dataset with multiple sample files (e.g., Std_soln_00, Std_soln_07, Std_soln_00a) where the same chemical is detected in different runs with varying Match.Factor scores, and you need to consolidate area values by compound identity rather than by individual peak detection.
    0 installs
41. ▌
    Ei Mass Spectra Structure Representation · holobiomicslab

    Use when you have raw or archived MSP spectral library files and need to load them into R for library searching, spectral matching, or batch reprocessing. Specifically, when you must extract precursor m/z values, peak intensity pairs, and spectrum metadata (e.
    0 installs
42. ▌
    Gc Column Polarity Specific Ri Filtering · holobiomicslab

    Use when you have a combined EI mass spectral library (MSP format) lacking experimental RI values, access to NIST ri.dat and USER.
    0 installs
43. ▌
    Mass Spectrometry Data Format Conversion · holobiomicslab

    Use when you have mass spectral libraries from multiple sources (e.g., NIST EI, RIKEN MS2, MoNA GC-MS or LC-MS/MS, GNPS mgf) that need to be consolidated for use in MS-DIAL, or you have a single library with incomplete or malformed metadata (e.
    0 installs
44. ▌
    Mass Spectrometry Data Quality Filtering · holobiomicslab

    Use when you have generated a complete feature table from mzML files (e.g., Asari 'full' feature table) and need to curate it for downstream analysis.
    0 installs
45. ▌
    Mass Spectrometry Match Factor Filtering · holobiomicslab

    Use when you have a GC-MS dataset with a Match.Factor column (output from Agilent Unknowns Analysis or equivalent) and need to retain only high-confidence compound identifications.
    0 installs
46. ▌
    Metabolomic Feature Extraction From Mzml · holobiomicslab

    Use when you have centroid mzML files from LC-MS acquisitions and need to detect, group, and quantify metabolomic features for a PCPFM experiment. Use it as the first feature-level processing step after file format conversion from raw instrument files (e.g., .raw to mzML via ThermoRawFileParser).
    0 installs
47. ▌
    Overlapped Peak Deconvolution Validation · holobiomicslab

    Use when after solving for the concentration distribution matrix C using least squares optimization (minimize ||overlapped_peaks - S·C||²), validate that the solution is physically meaningful and numerically accurate by checking whether S·C faithfully reconstructs the input overlapped peak.
    0 installs
48. ▌
    Retention Index Assignment And Filtering · holobiomicslab

    Use when after combining multiple EI or MS2 mass spectral libraries and you have access to NIST RI reference files (ri.dat and USER.DBU) and need to assign experimental retention indices to compounds.
    0 installs
49. ▌
    Spectral Library Compilation And Merging · holobiomicslab

    Use when you have multiple mass spectral library files in different formats (MSP, MGF, MOL folders) from sources like NIST, MoNA, RIKEN, or GNPS, and need to produce a single consolidated MSP file with complete SMILES, InChIKey, and experimental retention index (RI) annotations for metabolomics or.
    0 installs
50. ▌
    Spectral Library Metadata Reorganization · holobiomicslab

    Use when when ingesting mass spectral libraries (EI or MS2) where SMILES information is embedded in the Comment field rather than in a dedicated SMILES metadata field—particularly common in MoNA GC-MS and LC-MS/MS exports.
    0 installs
51. ▌
    Ablation Study Design And Interpretation · holobiomicslab

    Use when when you have a neural network or machine learning model with multiple tunable hyperparameters (layer size, regularization strength, dropout) or design choices (e.
    0 installs
52. ▌
    Annotation Candidate Comparative Scoring · holobiomicslab

    Use when you have pseudo-MS/MS spectra from LC-MS all-ion fragmentation (AIF) data that have been matched against one or more ion fragment databases (e.g., LipidPos, MassBank), generating multiple candidate annotations per feature.
    0 installs
53. ▌
    Batch Corrected Feature Table Validation · holobiomicslab

    Use when after applying batch correction (e.g., ComBat, SVA) to a merged feature table from non-targeted LC-MS/MS metabolomics data and before proceeding to univariate or multivariate statistical analysis.
    0 installs
54. ▌
    Bgc Identification From Genomic Sequence · holobiomicslab

    Use when you have assembled genome sequences (contigs or scaffolds in FASTA format) and want to identify putative BGCs and their precursor peptides before constructing a RiPP structure database for spectral matching.
    0 installs
55. ▌
    Bioconductor Backend Architecture Design · holobiomicslab

    Use when you are building a new mass spectrometry data backend or storage layer and need to integrate it with the Spectra ecosystem. Triggers include: (1) you have a novel data source (raw files, databases, web APIs) that should be accessible through Spectra objects;
    0 installs
56. ▌
    Bioconductor Object Structure Inspection · holobiomicslab

    Use when after constructing a SummarizedExperiment object from raw metabolomics data via buildExperiment, or after batch correction and ratio computation steps, inspect rowData, colData, and assays slots to verify that compound identities, sample annotations, and computed assay values (primary.
    0 installs
57. ▌
    Blind Search Mode Parameter Optimization · holobiomicslab

    Use when when you have tandem mass spectra from ribosomally synthesized peptides (RiPPs) and suspect the presence of unknown or non-standard post-translational modifications that would be missed by standard database search modes constrained to known modification classes.
    0 installs
58. ▌
    Chemical Noise Subformula Loss Filtering · holobiomicslab

    Use when you have MS/MS spectra with high chemical noise (spurious ions arising from incomplete ionization, in-source fragmentation, or instrument artifacts) and you possess accurate molecular formula or SMILES structure and adduct information for the precursor.
    0 installs
59. ▌
    Chromatographic Method Transfer Learning · holobiomicslab

    Use when you have experimental RT measurements from a source chromatographic method and need to predict RTs for the same molecules on a target chromatographic method, but lack a large calibration dataset (typical scenario: 10–100 molecules with ground truth RTs on both methods).
    0 installs
60. ▌
    Collision Cross Section Model Validation · holobiomicslab

    Use when after applying deimos.calibration.tunemix() to positive-mode or negative-mode tune mix data with known CCS reference compounds (m/z range typically 118–1522), verify that the resulting calibration model achieves the expected r-squared coefficient.
    0 installs
61. ▌
    Combined Table Extraction And Inspection · holobiomicslab

    Use when after constructing a metabCombiner object by grouping features from two metabData objects by m/z, and before proceeding to anchor selection, RT mapping, or alignment scoring.
    0 installs
62. ▌
    Compound Structural Similarity Retrieval · holobiomicslab

    Use when you have a collection of preprocessed MS/MS spectra with structural annotations (InChIKey, SMILES, or InChI) and need to identify pairs of compounds that are structurally related above a specified similarity threshold.
    0 installs
63. ▌
    Correlation Matrix Heatmap Visualization · holobiomicslab

    Use when after computing a correlation matrix (e.g., Pearson correlation across samples) on statistically significant LC-MS features, particularly when you need to inspect hierarchical dendrogram structure, validate cluster assignments from different flattening methods (constant-threshold vs..
    0 installs
64. ▌
    Cross Method Chromatographic Scalability · holobiomicslab

    Use when you have a pretrained RT-Transformer model checkpoint from a large, well-characterized chromatographic dataset (e.g., SMRT) and need to predict retention times for a different chromatographic method or instrument condition represented in a smaller, domain-specific dataset (e.g., PredRet).
    0 installs
65. ▌
    Database Schema Design For Spectral Data · holobiomicslab

    Use when you have MS/MS spectral library data currently stored in file-based formats (JSON, CSV, binary, MGF, MSP) and need to migrate to database-backed storage to support fast queries by metadata filters (precursor m/z, ion mode, retention time) and computed similarity scores against query.
    0 installs
66. ▌
    Double Bond Positional Isomer Generation · holobiomicslab

    Use when when constructing a comprehensive lipid spectral reference library that must disambiguate lipids differing only in carbon-carbon double-bond position (e.
    0 installs
67. ▌
    Embedding Space Dimensionality Reduction · holobiomicslab

    Use when when you have a collection of MS/MS spectra (in mzML or MGF format) and need to group or retrieve spectra from the same peptide, or when you need to perform large-scale similarity comparisons across millions of spectra without working directly in the original high-dimensional peak space.
    0 installs
68. ▌
    Experimental Design Metadata Integration · holobiomicslab

    Use when when you have LC-MS raw data and need to process it through a feature detection and quantification pipeline in KNIME, but lack a structured mapping between sample identifiers, experimental conditions, and the raw LC-MS runs.
    0 installs
69. ▌
    Feature Hashing Dimensionality Reduction · holobiomicslab

    Use when you have high-resolution tandem mass spectra (mzML, mzXML, or MGF format) and need to cluster or index millions of spectra efficiently without exhaustive pairwise comparison.
    0 installs
70. ▌
    Feature Matrix Normalization And Scaling · holobiomicslab

    Use when you have a heterogeneous feature matrix combining molecular descriptors (from RDKit/mordred) and chromatographic metadata (column length, temperature, pH, flow rate, particle size) with different physical units, ranges, and scales.
    0 installs
71. ▌
    Feature Metadata Parsing And Integration · holobiomicslab

    Use when after completing sample alignment in JPA (Part 5) or when ingesting a peaklist or aligned feature matrix from prior peak-picking runs, parse feature metadata to enable EIC export or multi-sample feature annotation.
    0 installs
72. ▌
    Feature Table Annotation Standardization · holobiomicslab

    Use when after Blueshift or Gravity processing has produced a feature abundance table with annotations, but before final reporting or integration with sample/injection metadata.
    0 installs
73. ▌
    Formula Database Chemical Noise Sampling · holobiomicslab

    Use when when you need to generate synthetic MS/MS spectra with chemical noise for validating denoising performance, benchmarking library matching algorithms, or testing edge cases where clean reference spectra exist but must be augmented with realistic contaminants.
    0 installs
74. ▌
    Function Wrapping And Binding Mechanisms · holobiomicslab

    Use when when you have Spectra objects in R and need to apply Python MS library functionality (spectral similarity scoring, filtering, normalization) without leaving the R environment, or when you want to create custom hybrid workflows that leverage both R and Python MS packages within a single.
    0 installs
75. ▌
    Gnps Spectral Library Compound Retrieval · holobiomicslab

    Use when you have GNPS library accession IDs (e.g. CCMSLIB00011906190) for a reference compound and a chemically or biologically modified analog, and need to load their full MS/MS spectra and structural annotations to set up a modification-finding analysis.
    0 installs
76. ▌
    High Resolution Mass Spectrum Processing · holobiomicslab

    Use when when you have high-resolution tandem mass spectra from proteomics experiments and need to search against a spectral library for both unmodified peptides and those with unknown or variable post-translational modifications.
    0 installs
77. ▌
    High Throughput Spectral Data Processing · holobiomicslab

    Use when when you have MGF-formatted mass spectrometry peak files (typically from proteomics experiments) numbering in the millions of spectra that require grouping into similar MS/MS clusters, and runtime must be kept under 15 minutes rather than hours.
    0 installs
78. ▌
    Identifier Format Parsing And Validation · holobiomicslab

    Use when you receive mass spectrometry data through heterogeneous identifier formats—specifically when the input could be a GNPS Task ID, a Universal Spectrum Identifier (USI), or a Feature-Based Molecular Networking (FBMN) identifier—and you need to programmatically determine which format was.
    0 installs
79. ▌
    Inchikey Normalization And Deduplication · holobiomicslab

    Use when you have an annotated MS/MS spectral dataset with structure metadata (InChI or SMILES records) linked to InChIKey identifiers, and you observe that some InChIKeys are associated with multiple or variant InChI strings due to curation inconsistencies, stereoisomerism notation differences, or.
    0 installs
80. ▌
    Inference Model Cpu Thread Configuration · holobiomicslab

    Use when when running Mass2SMILES inference on a TensorFlow-CPU build (e.g., delser292/mass2smiles:final container) and you need to optimize inference speed by controlling CPU core allocation.
    0 installs
81. ▌
    Installation Verification And Validation · holobiomicslab

    Use when after cloning the ENPKG repository and installing dependencies using uv sync or conda, before executing the workflow on metabolomics datasets.
    0 installs
82. ▌
    Isotope Labelling Feature Interpretation · holobiomicslab

    Use when after basepeak_finder has identified base peaks from isotope-labelled feature clusters with fold-change and intensity thresholds met.
    0 installs
83. ▌
    Lc Ms Feature Grouping By Retention Time · holobiomicslab

    Use when immediately after chromatographic peak detection (findChromPeaks) when you have detected peaks across multiple samples and need to identify which peaks represent the same feature across the sample cohort.
    0 installs
84. ▌
    Lda Convergence Monitoring And Iteration · holobiomicslab

    Use when after configuring LDA hyperparameters (alpha, beta, number of topics, iteration budget) and loading a preprocessed bag-of-fragments corpus with neutral losses extracted and noise filtered, initiate LDA training and apply convergence monitoring to determine when topic-fragment probability.
    0 installs
85. ▌
    Library Spectrum Database Format Parsing · holobiomicslab

    Use when you have experimental MS/MS spectra (from mzML, mzXML, or raw instrument formats) and wish to match them against a reference spectral library provided in MSP or CSV format. The skill is required as the first step before similarity scoring and candidate ranking.
    0 installs
86. ▌
    Mass Difference Calculation And Matching · holobiomicslab

    Use when you have centroided data-dependent acquisition (DDA) MS2 spectra from LC- or GC-HRMS and need to annotate detected features with PFAS-specific diagnostic fragments. Use it after feature detection (e.
    0 installs
87. ▌
    Mass Spectrometry Data Import And Export · holobiomicslab

    Use when use this skill at the start of any mass spectrometry analysis pipeline when you have raw spectral data in mzML, mzXML, msp, MGF, JSON, or metabolomics-USI format and need to load it into a Python environment for preprocessing, cleaning, filtering, or similarity comparison.
    0 installs
88. ▌
    Mass Spectrometry Data Structure Mapping · holobiomicslab

    Use when after feature extraction and peak recognition have produced detected MS/MS spectra (precursor m/z, charge, retention time, and fragment ion peaks), and you need to export these spectra for external spectral database searching, cross-platform comparison, or archival in a format compatible.
    0 installs
89. ▌
    Mass Spectrometry Feature Representation · holobiomicslab

    Use when after LC-MS feature clustering based on MS-DIAL peak character estimation, when you have grouped features that share similar chromatographic or spectral properties and need to select a single representative feature per cluster to reduce false positives and redundant annotations before.
    0 installs
90. ▌
    Mass Spectrometry Fragmentation Modeling · holobiomicslab

    Use when you are generating synthetic LC-MS/MS data for method validation, algorithm benchmarking, or co-fragmentation analysis, and need to model how specific biomolecules (peptides, nucleosides, or other chemical formulas) fragment under collision-induced dissociation.
    0 installs
91. ▌
    Mass Spectrometry Qc Criteria Definition · holobiomicslab

    Use when when setting up a new LC-MS QC workflow or modifying existing QC rules: you have access to internal standards and target analytes, know their expected retention times and m/z values, and need to establish pass/fail boundaries for sample acceptance before or concurrent with instrument runs.
    0 installs
92. ▌
    Mass Spectrometry Raw Data Preprocessing · holobiomicslab

    Use when when you have raw DIA mass spectrometry data files (.raw, .d, .
    0 installs
93. ▌
    Mass Spectrometry Spectrum Vectorization · holobiomicslab

    Use when you have high-resolution MS/MS spectra in mzML, mzXML, or MGF format and need to cluster or search across millions of spectra. The vectorization step is necessary before constructing nearest-neighbor indexes or computing pairwise distance matrices for spectrum clustering.
    0 installs
94. ▌
    Mass Spectrometry Workflow Orchestration · holobiomicslab

    Use when you have a collection of mzML or mzML.gz files from LC-IMS-MS/MS experiments and need to apply a consistent, reproducible sequence of feature detection, alignment, CCS calibration, isotope detection, and MS/MS deconvolution operations across multiple samples.
    0 installs
95. ▌
    Mass Spectrum Prediction Neural Networks · holobiomicslab

    Use when when you have molecular structures (SMILES, InChI, or chemical formula) and need to predict their tandem mass spectra for structural elucidation or compound ranking against databases. Use SCARF when operating at the chemical formula level;
    0 installs
96. ▌
    Mass To Charge Matching Tolerance Tuning · holobiomicslab

    Use when you are preparing to align two or more nontargeted LCMS datasets from the same analytical method using Eclipse and need to determine the m/z tolerance window.
    0 installs
97. ▌
    Metabolic Model Constraint Specification · holobiomicslab

    Use when you have a generic constraint-based metabolic model (SBML format) and cross-sectional omics data (RNA-seq, intracellular metabolomics, YSI or bioanalyzer extracellular flux measurements) for multiple biological samples and need to create sample-specific models that discriminate whether.
    0 installs
98. ▌
    Metabolite Abundance Threshold Filtering · holobiomicslab

    Use when you have intracellular metabolomics data paired with constraint-based metabolic model predictions and need to identify metabolically controlled reactions.
    0 installs
99. ▌
    Metabolite Edge Scoring Dbedges Bioedges · holobiomicslab

    Use when you have a measured m/z value from spatially-resolved metabolomics or mass spectrometry imaging and need to assign a molecular formula with high confidence. Use it specifically when you have access to a pre-constructed formula network (KnownSet database) linking 2.
    0 installs
100. ▌
     Metabolite Feature Treemap Visualization · holobiomicslab

     Use when after applying mpactr's filter suite (filter_mispicked_ions, filter_group, filter_cv, filter_insource_ions) to a peak table, use this skill when you need to summarize the overall filtering outcome across all ion categories and present a compact, area-proportional view of which ions passed.
     0 installs