Claude Skills by HolobiomicsLab

Use when ingesting PSM files from proteomics search engines (MS Amanda,

Use when when you have raw co-fractionation/mass-spectrometry elution

Use when you have two augmented versions of the same ion image (from

Use when you have preprocessed and normalized LC-MS metabolomics data

Use when when you have downloaded pre-trained Keras models and need to

Use when you have UPLC-HRMS data (ThermoFisher, Agilent, or MSConvert-compatible

Use when you have extracted molecular features (voxel projected areas,

Use when after converting or loading a Keras model to HDF5 TensorFlow

Use when you have transformer encoder components and a prediction head

Use when when you have MS/MS spectra from GNPS or other libraries and

Use when after training a Siamese neural network on MS/MS spectrum pairs,

Use when when you need to construct a dual-branch neural network encoder

Use when you have a trained deep learning model and want to quantify

'Use when you have a pretrained deep learning model, a reserved test

Use when you have preprocessed mass spectrometry spectra (tokenized m/z

Use when you have downloaded the LC-MS spectral peak dataset (DOI 10.25345/C5FD2F)

Use when you have a trained deep-learning model (e.g., MSNovelist) that

Use when you have unpaired mass spectrometry spectra and need to predict

Use when when you have preprocessed MS/MS spectral data (normalized peak

Use when you have paired tandem MS/MS spectra with known molecular fingerprints,

Use when you have paired mass-spectrometry spectral data (m/z and intensity

Use when you have a pre-trained deep learning encoder (e.g., TCN spectrum

Use when you have raw or preprocessed mass spectrometry feature matrices

Use when you are training a deep learning model using k-fold cross-validation

Use when you have cloned or loaded a deep-learning architecture extension

Use when you have a preprocessed metabolomics expression matrix with

Use when when you have a TransitionGroup structure containing normalized

Use when when you have an unknown compound's mass spectrum (m/z peaks

Use when you have metabolomic or expression feature data, sample-level

Use when training a CNN model from scratch on LCMS peak classification

Use when you have a pre-trained DNN model for retention time prediction

Use when when training a DNN on molecular properties (e.g., retention

'Use when training a DNN on retention time prediction or similar continuous

Use when when processing OMSLs (Open Mass Spectra Libraries) with heterogeneous

Use when when you have a binned MS/MS spectrum vector (e.g., 9948-dimensional

Use when when setting up a fresh clone of the ENPKG workflow repository

Use when when you have cloned a Python package repository and need to

Use when a bioinformatics package claims to install a large number of

Use when before launching the DaDIA pipeline or any multi-package R workflow

Use when when preparing to build LipidSpace or similar desktop/CLI applications

Use when when you need to document or reproduce a Python-based research

'Use when before launching a multi-tool computational workflow (e.g.,

Use when you encounter a scientific implementation (particularly deep

Use when preparing a scientific application (such as a metabolite annotation

Use when building a Streamlit application that must support both cloud

Use when after spectral database dereplication (using Spectra) and compound

Use when when performing metabolite identification in mass spectrometry

Use when you have a derivatizing matrix (e.g., TAHS or other publicly

Use when when working with mass spectrometry imaging data from metabolites

Use when after lipid matching is complete and you have a table of matched