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Claude Skills by HolobiomicsLab

github.com/HolobiomicsLab
12,704 skillsA× 12,683B× 13C× 2D× 60 installs5,180 views
Cross Dataset Score Distribution ComparisonA

'Use when when you have applied multiple scoring functions (e.g., strain

ai-agentstestinggit
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15
Cross Domain Masst Output ParsingA

Use when you have executed batch searches against one or more domain-specific

ai-agentspythongit
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15
Cross Domain Metadata HarmonizationA

Use when when you have submitted the same MS/MS spectrum query to multiple

ai-agentspythongit
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15
Cross Domain Metadata IntegrationA

Use when when you have conducted batch MS/MS searches across one or more

ai-agentspythongo
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15
Cross Domain Token MappingA

Use when when building a unified sequence model (e.

ai-agentsgit
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15
Cross File Version Consistency CheckingA

Use when before initiating a release branch workflow for a multi-module

ai-agentsgit
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15
Cross Instrument Data HarmonizationA

Use when you have mass spectrometry spectral data from multiple instrument

ai-agentsgogit
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15
Cross Language Data Format InteroperabilityA

Use when you have mass spectrometry data (LC–MS/MS, ion mobility, DIA)

ai-agentspythondocker
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15
Cross Language Function Invocation And ValidationA

Use when your R-based Spectra analysis workflow requires a specific mass

ai-agentspythongo
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15
Cross Language Implementation CompatibilityA

Use when when a new file format specification has multiple language implementations

ai-agentspythonrust
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15
Cross Language Interface DesignA

Use when when you have domain-specific functionality (e.g., spectral

ai-agentspythongo
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15
Cross Language Interface ImplementationA

Use when you have a mature R analysis pipeline (e.g., using Spectra objects

ai-agentspythongo
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15
Cross Language Workflow OrchestrationA

Use when you have multi-language code implementations (R and MATLAB scripts)

ai-agentsgitdocumentation
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15
Cross Member Metabolic Dependency ResolutionA

Use when when you have consensus metabolic reconstructions for multiple

ai-agentsgoreact
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15
Cross Method Chromatographic ScalabilityA

Use when you have a pretrained RT-Transformer model checkpoint from a

ai-agentspythongit
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15
Cross Method Rt CalibrationA

Use when when you have predicted retention times from a DNN model trained

ai-agentspythongo
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15
Cross Modal Alignment TrainingA

Use when after completing pretraining and fine-tuning stages when you

ai-agentsbashgit
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15
Cross Omics Feature AlignmentA

Use when you have preprocessed multiomics datasets from distinct biomolecular

ai-agentsgogit
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15
Cross Omics Feature MatchingA

Use when when you have two feature matrices from different omics modalities

ai-agentsexpressgit
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15
Cross Omics Strain MappingA

Use when when you have paired genomics (AntiSMASH BGC annotations) and

ai-agentspythongit
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15
Cross Organism Network ComparisonA

Use when you have selected two organisms whose metabolic networks are

ai-agentsgojava
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15
Cross Origin Policy OverrideA

Use when you are loading index.html locally in a browser and WebWorker

ai-agentsjavascriptgo
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15
Cross Platform Build Environment SetupA

Use when when you have a Qt5 C++ project (such as Maven GUI or Maven

ai-agentsc++sql
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15
Cross Platform Build TargetingA

Use when you have a Windows-only .NET Framework application that must

ai-agentsc#docker
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15
Cross Platform CompilationA

Use when when releasing a new version of a tool, onboarding to a new

ai-agentsgodocker
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15
Cross Platform Dependency DetectionA

Use when when developing a standalone scientific application that relies

ai-agentspythongit
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15
Cross Platform Reproducibility ConfigurationA

Use when when you have documented pinned package versions for a Python-based

ai-agentspythongit
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15
Cross Platform Software Capability MappingA

Use when you are designing a new tool for FT-ICR MS analysis (or similar

ai-agentspythongo
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15
Cross Reference Publication LinkingA

Use when when cataloging a suite of related bioinformatics tools or web

ai-agentsgogit
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15
Cross Sample Alignment Matrix ConstructionA

Use when you have already generated per-sample MS2 fingerprints (count

ai-agentspythongit
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15
Cross Sample Feature AlignmentA

Use when you have run mass detection and chromatogram building independently

ai-agentsgoc++
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15
Cross Sample Feature MatchingA

Use when you have detected feature tables from two or more LC-IMS-MS/MS

ai-agentspythongo
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15
Cross Sample Metabolite MatchingA

Use when after feature extraction (MS1 peak picking, MS2 recognition,

ai-agentsgit
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15
Cross Script Consistency VerificationA

Use when when a deep learning pipeline processes mass spectrometry spectra

ai-agentspythongit
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15
Cross Software Feature MatchingA

Use when you have collected feature lists in CSV format from two or more

ai-agentsgogit
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15
Cross Spectrum Negative Generation Within Mz WindowA

Use when when preparing augmented training data for a Siamese rescore

ai-agentspythongo
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15
Cross Spectrum Negative MiningA

Use when when training a Siamese architecture rescore model for MS/MS-based

ai-agentspythongit
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15
Cross Split Metric AggregationA

'Use when when you have a pre-trained model and need to report stable,

ai-agentspythongit
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15
Cross Table Metadata HarmonizationA

Use when when you have obtained raw metabolite abundance data in a format

ai-agentsgit
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15
Cross Tool Performance ComparisonA

Use when when you have raw tandem MS metabolomics data in vendor formats

ai-agentspythongo
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15
Cross Tool Result Concordance AnalysisA

Use when you have executed multiple NPDtools database search pipelines

ai-agentspythongo
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15
Cross Validated Model Performance Evaluation 10foldA

Use when when you have trained a neural network or regression model to

ai-agentspythongit
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15
Cross Validation Benchmark EvaluationA

Use when you have developed a predictive model and need to compare its

ai-agentspythongo
0
15
Cross Validation Model AggregationA

Use when after training multiple neural network models via k-fold cross-validation

ai-agentspythongo
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15
Cross Validation Parameter TuningA

Use when when building Cox-PH or Cox-nnet survival models from expression

ai-agentspythongo
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15
Cross Validation Performance EvaluationA

Use when when you have paired microbiome and metabolome count data and

ai-agentspythongo
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15
Cross Validation Result InterpretationA

Use when after running k-fold repeated cross-validation on a development

ai-agentsgotesting
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15
Cross Validation Strategy SelectionA

Use when when preparing to train supervised binary classification models

ai-agentsgogit
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15
Cross Validation Workflow ExecutionA

Use when you have paired microbiome (16S rRNA/metagenomic) and metabolome

ai-agentspythontesting
0
15
Cross View Similarity ScoringA

Use when you have an experimental mass spectrum (query) and a set of

ai-agentspythongo
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15