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Claude Skills by HolobiomicsLab

github.com/HolobiomicsLab
12,704 skillsA× 12,683B× 13C× 2D× 60 installs6,254 views
Structure Standardization ValidationA

Use when you have raw or heterogeneous molecular structure inputs (SMILES

ai-agents
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Structure Validation And CanonicalizationA

Use when ingesting heterogeneous raw chemical structures from external

ai-agentsperformance
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Structured Data Compilation From ReadmeA

Use when when a scientific software repository documents multiple standalone

ai-agentspythongo
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15
Structured Data Element CheckingA

Use when you have generated or received a mass spectrometry data file

ai-agentspythonrust
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Structured Data Matrix ConstructionA

Use when you have raw LipidSearch or LIQUID output files (CSV or TSV

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Structured Data Quality AssessmentA

Use when when you have deposited a collection of JSON project documents

ai-agentsgitapi
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Structured Data SerializationA

Use when when you have mwTab-formatted Mass Spectrometry or Nuclear Magnetic

ai-agentspythongit
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Structured Data Table CreationA

Use when you have obtained a raw reference library file (such as the

ai-agentsgitdocumentation
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Structured Inventory CompilationA

Use when when you need to understand the modular composition of a multi-component

ai-agentspythongo
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Structured Logging And Metric ExtractionA

Use when when executing a multi-converter annotation workflow on mass

ai-agentsgogit
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Structured Molecule Relationship EvaluationA

Use when when you have tandem mass spectra (MSMS) from related or candidate

ai-agentsgogit
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Structured Report GenerationA

Use when after applying jsonschema validation to a parsed mwTab file

ai-agentspythongo
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Structured Result ValidationA

Use when after retrieving a JSON or tabular response from a web service

ai-agentsjavagit
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Study Size Weighted AveragingA

Use when you have metabolomics results from multiple independent studies

ai-agentsgit
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Sub Cluster Assignment ExtractionA

Use when after PRESTO-TOP topic modelling has been run on redundancy-filtered

ai-agentsgogit
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Sub Network Detection From Scored GraphsA

Use when you have a GLASSO-inferred sparse network graph and associated

ai-agentspythongo
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Subformula Assignment Neural NetworksA

Use when when you have MS/MS spectra with assigned precursor formulas

ai-agentsgogit
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Subformula Enumeration And Mass CalculationA

'Use when when performing chemical denoising of MS/MS spectra: after

ai-agentspythongit
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Subformula EnumerationA

Use when when performing chemical noise removal on MS/MS spectra and

ai-agentspythongo
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Subpfam Functional Resolution AugmentationA

Use when you have annotated genes with Pfam domains but require higher

ai-agentsgodatabase
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Substrate Concentration NormalizationA

Use when you have LC-MS normalized intracellular metabolite abundance

ai-agentspythongo
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Substructural Motif AnnotationA

Use when you have created a GNPS molecular network (classical or feature-based

ai-agentspythonnode
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Substructure Annotation IntegrationA

Use when you have (1) a GNPS molecular network (classical or feature-based)

ai-agentspythongo
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Summarized Experiment Data Structure HandlingA

Use when you have high-dimensional metabolomics or genomics data stored

ai-agentsgitdocumentation
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Summarized Experiment Initialization And PopulationA

Use when when beginning a metabolomics analysis workflow in maplet, you

ai-agentsgit
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Summarized Experiment Object ConstructionA

Use when when you have imported a tab-delimited metabolomics file (via

ai-agentsgit
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Summarized Experiment Object HandlingA

Use when you have cross-validated, filtered metabolomic NMR or MS data

ai-agentstestinggit
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Summarized Experiment Object ManipulationA

Use when when working with metabolomics, proteomics, or other high-throughput

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Summarized Experiment SubsettingA

Use when when you have a SummarizedExperiment containing metabolomic

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Summarizedexperiment Assay ManipulationA

Use when when working with multi-batch metabolomics studies where you

ai-agentsgit
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Summary Statistics Table ConstructionA

Use when when you need to quantify and compare the effect of multiple

ai-agentsgogit
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Summary Visualization Artifact GenerationA

Use when you have completed batch spectral searches against multiple

ai-agentspythongo
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Survival Data PreparationA

Use when when you have clinical survival outcomes (event status and follow-up

ai-agentspythonexpress
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Suspect Database MatchingA

Use when you have LC-MS peak/feature data, a curated suspect compound

ai-agentsgogit
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Suspect List Format ConversionA

Use when you have generated a set of transformation products (TPs) from

ai-agentsgogit
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Swath Ms Spectrum DeconvolutionA

Use when you have SWATH-MS raw data (mzML or vendor format) from an untargeted

ai-agentsgoreact
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Syntax Tree Construction ParsingA

Use when you have a domain-specific language (DSL) grammar specification

ai-agentssqlexpress
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Synthetic Lcmsms Data GenerationA

Use when you need to create defined LC-MS/MS datasets with known molecular

ai-agentspythongo
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Synthetic Spectrum GenerationA

Use when when you need to create benchmark LC-MS/MS datasets with controlled,

ai-agentspythongo
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Synthetic Training Instance GenerationA

Use when when you have a small set of matched reference features (isolated,

ai-agentspythongit
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System Call Invocation Via System2A

Use when you need to query or extract data from Thermo Fisher Scientific

ai-agentsc#git
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System Configuration DocumentationA

Use when after successfully installing and validating all components

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System Environment ConfigurationA

Use when you need to execute a complex computational chemistry workflow

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System Library Dependency MappingA

Use when a Shiny application or similar cross-platform tool is restricted

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System Path Environment ConfigurationA

'Use when when setting up imzML Writer for the first time on a new machine,

ai-agentspythonshell
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Systematic Mass Calibration And Drift CorrectionA

Use when when processing multiple LC-MS samples in a cohort study and

ai-agentspythongit
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Systems Biology Model StandardizationA

Use when you have multiple draft metabolic reconstructions of community

ai-agentsgoreact
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T Test Interpretation MetabolomicsA

Use when you have preprocessed, normalized, and imputed metabolite measurements

ai-agentsgotesting
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Tab Delimited Export Formatting For MetabolomicsA

Use when after completing batch normalization and quality control filtering

ai-agentsgit
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Tab Delimited Metabolomics File ParsingA

Use when when you have raw metabolomics measurements in tab-delimited

ai-agentsgit
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