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Use when working with TAPE (Tasks Assessing Protein Embeddings) for protein representation learning, benchmark evaluation, or sequence embedding. Covers training and evaluating transformer, LSTM, ResN
Use with AI
Install the MCP server or CLI to instantly fetch TAPE documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/tape
AlphaPept — Python-based, open-source proteomics pipeline for DDA mass spectrometry data analysis. Provides feature detection, peptide identification via database search, deep learning-based scoring,
2 shared topics • 1 shared operation
Use when working with mokapot — mokapot -- Python package for semi-supervised
2 shared topics • 1 shared operation
Percolator — semi-supervised machine learning tool for rescoring peptide-spectrum matches (PSMs) from shotgun proteomics database searches. Uses target-decoy competition with SVM classification to sep
2 shared topics • 1 shared operation
Prosit — deep learning framework for predicting MS2 fragment ion spectra and indexed retention times (iRT) from peptide sequences. Enables in silico spectral library generation for any organism and pr
2 shared topics • 1 shared operation
PyTorch Geometric (PyG) — graph neural network library built on PyTorch for learning on graphs and irregular structures. Provides message-passing layers (GCN, GAT, GraphSAGE, GIN, Transformer), mini-b
2 shared topics • 1 shared operation