Claude Skills by HolobiomicsLab

Use when when you have a collection of tokenised BGCs (each gene represented

Use when after executing a molecular networking workflow on GC-MS data

Use when you have a metabolic or biological network encoded as pairwise

Use when after constructing or loading a network object (from adjacency

Use when after retrieving a molecular network file (GraphML or JSON format)

Use when when you have computed betweenness centrality (or other igraph

Use when after identifying statistically significant features and assigning

Use when you have preprocessed MS/MS spectra pairs (unknown and known

Use when you have raw mzML files and feature tables (CSV from mzMine

Use when you have a working base MPNN model (e.g., chemprop) and need

Use when when you have retrieved a model definition file (e.g., TransGNet.py)

Use when you have a pretrained TCN spectrum encoder from formula prediction

Use when you have MS/MS spectra with unknown precursor m/z values and

Use when when training a multilayer perceptron neural network on paired

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

Use when when you need to benchmark multiple encoder types (e.g., FFN

Use when when you have a trained neural network and need to quantify

Use when when you have preprocessed joint ST/SM AnnData objects (output

Use when when training a multilayer perceptron to predict metabolomic

Use when when you have paired or unpaired MS/MS spectra and need to compute

Use when you have (1) a molecular structure input in SMILES, InChI, or

Use when when you have annotated representative LCMS samples (raw mzML

Use when when replacing deprecated model components (e.

Use when when you have a neural network layer definition (parameters,

Use when after deploying a TensorFlow-backed classification service,

Use when you have a trained conformer-based peak-picking model (in ONNX

Use when you have LC-MS feature tables (m/z and retention time columns)

Use when you have a pre-trained neural network model (e.g., MSBERT weights

Use when you have pre-trained MSGO model weights (PFAS or lipid variant)

Use when after converting Keras models to HDF5 TensorFlow 2.0 format

Use when you have downloaded LC-MS spectral peak data (DOI 10.25345/C5FD2F

Use when when building an end-to-end deep learning model that must predict

Use when after implementing a neural network component that will feed

Use when when you have 512-dimensional (or other fixed-size) representation

Use when implementing or modifying a Siamese model (such as SiameseModel

Use when when training a deep neural network on paired MS/MS spectra

Use when when you have an unknown MS/MS spectrum (m/z and intensity pairs),

Use when after training a NeatMS neural network model on labelled peak

Use when your input is a corpus of MS/MS spectra with annotated molecular

Use when you have trained MLPNN models on paired microbiome-metabolome

Use when when building Word2Vec or embedding-based spectral similarity

Use when during MS/MS spectral preprocessing when converting raw spectra

Use when when converting MS/MS spectra into spectral documents for Spec2Vec

Use when after LDA modeling has inferred a set of Mass2Motifs (in JSON

Use when you have a collection of annotated MS/MS spectra with precursor

Use when preparing MS/MS spectra for bag-of-fragments conversion and

Use when after loading and noise-filtering raw MS/MS spectra (in .mgf,

Use when you have MS2 spectra data (MGF/mzML format) and aligned feature

Use when you have tandem mass spectra with precursor m/z and observed

Use when you have a tandem mass spectrum (MSMS) loaded via USI and wish