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생산성 및 협업 · SKILL.md

protein-sequence-function

protein-sequence-function

Use for PaddleHelix protein sequence pretraining, prediction, protein function workflows, tokenizer/model guidance, and safe protein input validation.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: protein-sequence-function description: "Use for PaddleHelix protein sequence pretraining, prediction, protein function workflows, tokenizer/model guidance, and safe protein input validation." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Protein Sequence Function

Use this sub-skill when the task asks about PaddleHelix TAPE-style protein sequence models, protein property prediction, protein function prediction apps, protein sequence tokenization, FASTA/plain sequence validation, PPI routing, or HelixProtX high-level protein modality routing.

Route First

  • Use this sub-skill for TAPE train/eval/predict command construction, model config checks, ProteinTokenizer behavior, and protein sequence model-family orientation.
  • Use this sub-skill for DeepFRI, ProteinSIGN, and PTHL protein function prediction command anatomy, data roles, checkpoints, and missing-argument diagnosis.
  • Route biomolecular 3D structure prediction, HelixFold, and HelixFold3 input/output planning to ../structure-prediction/SKILL.md.
  • Route LinearRNA folding/partition tasks to ../linear-rna/SKILL.md; route compound/drug workflows to ../compound-drug-discovery/SKILL.md.
  • Treat PPI S2F requests as not-yet-released in the scoped PaddleHelix evidence; explain the gap and ask whether the user wants adjacent sequence/function guidance instead.

Safe First Steps

  1. Classify the request as TAPE sequence modeling, graph-based function prediction, PPI, or HelixProtX multimodal protein routing.
  2. Validate sequences and model config before constructing a training/eval/predict command.
  3. Check that all user-provided data, checkpoint, graph, and label paths are explicit; do not assume app defaults are valid.
  4. Confirm before starting downloads, training, GPU/distributed jobs, graph preprocessing over PDB, or HelixProtX demos.

Bundled Helper

Use the safe validator before heavyweight commands. It performs local parsing only and never downloads data, trains, mutates checkpoints, or imports Paddle/PGL.

python sub-skills/protein-sequence-function/scripts/validate_protein_inputs.py \
  --sequence ACDJX \
  --show-token-ids

For TAPE prediction preflight, add --workflow tape-predict, --config, --predict-model, and either --predict-data, --fasta, or --sequence. For function-prediction checks, use --workflow function-test with --model-name, --label-data-path, --test-file, and --protein-chain-graphs; missing --model-name or --label-data-path is a real evaluation blocker.

Reference Map

  • references/workflows.md: TAPE and function-prediction command anatomy, data/checkpoint/model roles, PPI and HelixProtX routing.
  • references/data-formats.md: sequence, tokenizer, TAPE NPZ/config, function-prediction graph and label formats.
  • references/api-reference.md: ProteinTokenizer, protein sequence model class family, task heads, criteria, metrics, and dataloader orientation.
  • references/troubleshooting.md: unknown residues, missing data/checkpoints, Paddle/PGL versions, GPU/distributed flags, and PDB graph requirements.
  • scripts/validate_protein_inputs.py: safe local validator for FASTA/plain sequences, token IDs, TAPE configs, optional JSON/config parsing, and function workflow path checks.

Evidence Labels

Distilled from these repo-relative evidence labels: apps/pretrained_protein/tape/, apps/protein_function_prediction/, apps/protein_protein_interaction/, apps/helixprotx/, pahelix/utils/protein_tools.py, pahelix/model_zoo/protein_sequence_model.py, and tutorials/protein_pretrain_and_property_prediction_tutorial.ipynb.

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