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Claude Skills by HolobiomicsLab

github.com/HolobiomicsLab
12,704 skillsA× 12,683B× 13C× 2D× 60 installs5,702 views
Laser Ablation Isotope Image InterpretationA

Use when you have imported a raw LA-ICP-MS raster image (line-by-line,

ai-agentspythongo
0
15
Latent Dirichlet Allocation Model TrainingA

Use when when you have preprocessed MS/MS spectral data (filtered, noise-reduced,

ai-agentspythongo
0
15
Latent Dirichlet Allocation Topic InferenceA

Use when you have a preprocessed corpus of mass spectrometry spectra

ai-agentspythongo
0
15
Latent Feature InterpretationA

Use when you have imaging mass spectrometry (IMS) data preprocessed into

ai-agentsgitdatabase
0
15
Latent Group Discovery From Omics DataA

Use when you have a preprocessed metabolomics feature matrix and sample

ai-agentsgotesting
0
15
Latent Space Dimensionality ReductionA

Use when you have imaging mass spectrometry (IMS) datasets where peak

ai-agentsgonode
0
15
Lc Gradient Vector Encoding And DecodingA

Use when when preparing LC gradient configurations for Bayesian optimization,

ai-agentspythongo
0
15
Lc Hrms 2d Area StandardizationA

Use when after detecting local-maxima in LC-HRMS profile mode datasets

ai-agentspythongo
0
15
Lc Hrms Data Preprocessing PipelineA

Use when you have raw LC-HRMS metabolomics data in .mzML or .abf format

ai-agentsjavadocker
0
15
Lc Hrms Data Processing EvaluationA

Use when you have processed the same set of untargeted LC/HRMS files

ai-agentsgogit
0
15
Lc Hrms Metabolomics Data ProcessingA

Use when you have LC-HRMS raw data files (.mzML or .abf format) from

ai-agentsgojava
0
15
Lc Ms Adduct Pattern DetectionA

Use when when you have statistically significant features from multi-assay

ai-agentspythongit
0
15
Lc Ms Data CalibrationA

Use when when you have paired LC-MS measurements from labeled and unlabeled

ai-agentsgoexpress
0
15
Lc Ms Data Pipeline ArchitectureA

Use when you have vendor-format LC-MS acquisition files (.raw, .d, .ms)

ai-agentspythonapi
0
15
Lc Ms Data PreprocessingA

'Use when you have raw mzML files and corresponding feature tables (CSV

ai-agentspythongit
0
15
Lc Ms Data Structure ValidationA

Use when before launching TARDIS peak detection on a new LC–MS dataset

ai-agentsgit
0
15
Lc Ms Dataset Acquisition And CurationA

Use when when beginning an untargeted LC-MS metabolomics study and need

ai-agentspythongo
0
15
Lc Ms Eic Plot InterpretationA

Use when after executing TARDIS in screening_mode = TRUE on centroided

ai-agentsgogit
0
15
Lc Ms Feature Alignment Cross DatasetA

Use when you have two peak-picked, conventionally aligned LC-MS metabolomics

ai-agentsgogit
0
15
Lc Ms Feature Extraction And AlignmentA

Use when you have centroid mzML files from LC-MS experiments (converted

ai-agentspythongit
0
15
Lc Ms Feature Grouping And CompoundingA

Use when after chromatographic peak detection on preprocessed LC-MS data,

ai-agentsgit
0
15
Lc Ms Feature Grouping By Retention TimeA

Use when immediately after chromatographic peak detection (findChromPeaks)

ai-agentsgogit
0
15
Lc Ms Feature M Z Rt ExtractionA

Use when you have preprocessed LC-MS intensity data (e.

ai-agentspythontesting
0
15
Lc Ms Feature Quality AssessmentA

Use when you have generated feature tables from LC-MS data using different

ai-agentsgodocker
0
15
Lc Ms Feature Quality ScoringA

Use when immediately after peak detection and feature table generation

ai-agentspythongit
0
15
Lc Ms Gradient Encoding Vector RepresentationA

Use when when you have a set of candidate LC gradients (parameter combinations)

ai-agentspythongo
0
15
Lc Ms Mass Matching Reference BuildingA

Use when at the start of an untargeted LC-MS annotation pipeline when

ai-agentsdatabase
0
15
Lc Ms Output ValidationA

Use when after executing a Nextflow-based LC-HRMS metabolomics workflow

ai-agentsdockertesting
0
15
Lc Ms Peak Feature EngineeringA

Use when you have LC-MS feature tables with m/z and retention time coordinates

ai-agentspythongo
0
15
Lc Ms Peak QuantificationA

Use when after a CNN-Transformer peak detection model has been run on

ai-agentspythongo
0
15
Lc Ms Profile Data SegmentationA

Use when you have raw profile (not centroided) LC-MS data in .mzML format

ai-agentspythongo
0
15
Lc Ms Quality Metric ComputationA

Use when after performing peak detection on centroided .mzML LC-MS data

ai-agentsgogit
0
15
Lc Ms Retention Time AdjustmentA

Use when you have centroided .mzML LC–MS data with multiple sample runs

ai-agentsgogit
0
15
Lc Ms Roi Annotation InterpretationA

Use when when you have extracted LC-MS ROI windows (m/z × retention time

ai-agentspythongo
0
15
Lc Ms Scan Acquisition OrchestrationA

Use when when you have a curated list of chemical compounds (real or

ai-agentspythongo
0
15
Lc Ms Spectral Data ImportA

Use when you have raw LC-MS/MS spectral data in .mgf format (or vendor-specific

ai-agentspythonc++
0
15
Lchrms Chromatographic Peak Boundary ExtractionA

Use when you have a set of target molecules with known molecular formula,

ai-agentsgogit
0
15
Lcims Msms Data Preprocessing Peak DetectionA

Use when you have loaded mzML.gz or HDF5-formatted raw LC-IMS-MS/MS data

ai-agentspythongo
0
15
Lcms Data Format HandlingA

Use when you have raw LC-MS data from a vendor instrument or in netCDF

ai-agentsgogit
0
15
Lcms Data Format ParsingA

Use when when you have raw LC/MS data in mzML format and need to execute

ai-agentspythongo
0
15
Lcms Feature ClassificationA

Use when you have an LCMS feature table annotated with MS2 spectral data

ai-agentsgogit
0
15
Lcms Feature Detection And QuantificationA

Use when you have raw LC-MS data (mzML or equivalent format) from a metabolomics

ai-agentsgitperformance
0
15
Lcms Feature ExtractionA

Use when when you have raw LC-MS chromatographic data (mzML or vendor

ai-agentspythongo
0
15
Lcms Feature Probability ScoringA

Use when you have an untargeted LC/MS feature table (m/z, retention time,

ai-agentspythonreact
0
15
Lcms Feature Relationship ExportA

Use when after ISFrag has completed identification of in-source fragment

ai-agentsgogit
0
15
Lcms Feature Table ConstructionA

Use when you have centroided, single-polarity mzML files from DDA LC-MS

ai-agentsgodocker
0
15
Lcms Feature Table ParsingA

Use when you have raw nontargeted LCMS feature tables from one or more

ai-agentspythongit
0
15
Lcms Metabolomics Data ProcessingA

Use when you have raw LC-HRMS metabolomics data in .mzML or .

ai-agentsdockerperformance
0
15
Lcms Peak Alignment And AnnotationA

Use when you have an XCMS-processed feature set (XCMSet object) from

ai-agentsgogit
0
15
Lcms Peak Detection And AlignmentA

Use when you have one or more raw mzXML or mzML LCMS data files (from

ai-agentsgogit
0
15