Claude Skills by HolobiomicsLab

Use when when you have installed a Python package (e.g., via pip or conda)

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

'Use when when you have access to a research repository or README documenting

Use when when you need to execute a multi-backend visualization library

Use when when you have cloned a scientific Python repository (e.g., ROIAL-NMR)

Use when you need to filter compounds during Pickaxe network expansion

Use when when you have classification predictions and ground-truth labels

Use when implementing online task queue deployments (RQ + Redis) where

Use when when you have Thermo Fisher RAW mass spectrometry files and

Use when you have developed new scoring logic (e.g., average inchikey

Use when when you have developed or obtained a new Python package that

Use when when you have completed spectral data preprocessing in Jupyter

Use when after constructing a peak properties dictionary via csv_to_peak_properties

Use when you need to enable optional modules in Pyteomics that depend

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

Use when when setting up a new computational environment for tandem MS/MS

Use when when you need to validate that a Python package (or update to

Use when when you have cloned a Python package repository locally and

Use when when you need to verify a Python package installs successfully

Use when when you have LC-MS/MS data in MZmine-generated MGF and CSV

Use when you have a mature Python package (e.g., Mummichog 2.x) that

Use when when you have mass spectrometry data in R's Spectra format but

Use when when a Shiny R application needs to use Python libraries that

Use when when you have an indexed gzip file (mzML.gz with internal index

Use when you have per-sample model predictions and metabolite signal

Use when you have a Python webservice codebase (e.g., a Flask, Django,

Use when you have MS/MS spectral library data currently stored in multiple

Use when you need to serialize heterogeneous data (e.g., index integers

Use when after rewriting or modifying a Python module (such as calculate_feature_overlap.py

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

Use when you have raw mass spectrometry spectral data in common formats

Use when a PyTorch-based model (such as a graph neural network trained

Use when when you have a pre-trained GNN model checkpoint and need to

Use when after instantiating a PyTorch model (such as TransG-Net) with

Use when you have constructed molecular graphs with atom features (atomic

Use when you have a pretrained PyTorch model with released weights (e.g.,

Use when when setting up a computational environment to run pre-trained

Use when you have a pretrained GNN-RT model trained on a reference molecular

Use when you have preprocessed MS/MS spectral data (m/z and intensity

Use when after defining a multi-branch neural network architecture (e.

Use when when you have a pre-trained PyTorch model checkpoint (e.g.,

Use when when you have preprocessed molecular graph representations (from

Use when when you need to extract both local spatial patterns and global

Use when when constructing a composite loss function for contrastive

Use when you have a PyTorch model architecture (pretrained or freshly

Use when when you have molecular structure inputs (SMILES strings, molecular

Use when when training a multi-component deep learning model where some

Use when when you have parsed molecular graph representations (atom nodes,

Use when after implementing a transformer encoder backbone with masking

Use when when building a graph-based molecular property prediction model