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Datasets:
GleghornLab
/
protein_concept_probing

Tasks:
Text Classification
Token Classification
Modalities:
Text
Time-series
Formats:
parquet
Size:
100K - 1M
Tags:
biology
protein
probing
interpretability
Libraries:
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pandas
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metadata 
license: other
license_name: cc-by-4.0-and-apache-2.0
license_link: LICENSE
pretty_name: Protein concept probing
task_categories:
  - text-classification
  - token-classification
tags:
  - biology
  - protein
  - probing
  - interpretability
configs:
  - config_name: functional_sites
    data_files:
      - split: train
        path: functional_sites/train.parquet
      - split: validation
        path: functional_sites/validation.parquet
      - split: test
        path: functional_sites/test.parquet
  - config_name: go_bp
    data_files:
      - split: train
        path: go_bp/train.parquet
      - split: validation
        path: go_bp/validation.parquet
      - split: test
        path: go_bp/test.parquet
  - config_name: go_cc
    data_files:
      - split: train
        path: go_cc/train.parquet
      - split: validation
        path: go_cc/validation.parquet
      - split: test
        path: go_cc/test.parquet
  - config_name: go_mf
    data_files:
      - split: train
        path: go_mf/train.parquet
      - split: validation
        path: go_mf/validation.parquet
      - split: test
        path: go_mf/test.parquet
  - config_name: interpro_active_site
    data_files:
      - split: train
        path: interpro_active_site/train.parquet
      - split: validation
        path: interpro_active_site/validation.parquet
      - split: test
        path: interpro_active_site/test.parquet
  - config_name: interpro_binding_site
    data_files:
      - split: train
        path: interpro_binding_site/train.parquet
      - split: validation
        path: interpro_binding_site/validation.parquet
      - split: test
        path: interpro_binding_site/test.parquet
  - config_name: interpro_conserved_site
    data_files:
      - split: train
        path: interpro_conserved_site/train.parquet
      - split: validation
        path: interpro_conserved_site/validation.parquet
      - split: test
        path: interpro_conserved_site/test.parquet
  - config_name: interpro_domain
    data_files:
      - split: train
        path: interpro_domain/train.parquet
      - split: validation
        path: interpro_domain/validation.parquet
      - split: test
        path: interpro_domain/test.parquet
  - config_name: interpro_family
    data_files:
      - split: train
        path: interpro_family/train.parquet
      - split: validation
        path: interpro_family/validation.parquet
      - split: test
        path: interpro_family/test.parquet
  - config_name: interpro_homologous_superfamily
    data_files:
      - split: train
        path: interpro_homologous_superfamily/train.parquet
      - split: validation
        path: interpro_homologous_superfamily/validation.parquet
      - split: test
        path: interpro_homologous_superfamily/test.parquet
  - config_name: interpro_repeat
    data_files:
      - split: train
        path: interpro_repeat/train.parquet
      - split: validation
        path: interpro_repeat/validation.parquet
      - split: test
        path: interpro_repeat/test.parquet
  - config_name: lipidation
    data_files:
      - split: train
        path: lipidation/train.parquet
      - split: validation
        path: lipidation/validation.parquet
      - split: test
        path: lipidation/test.parquet
  - config_name: localization
    data_files:
      - split: train
        path: localization/train.parquet
      - split: validation
        path: localization/validation.parquet
      - split: test
        path: localization/test.parquet
  - config_name: metal_ion_binding
    data_files:
      - split: train
        path: metal_ion_binding/train.parquet
      - split: validation
        path: metal_ion_binding/validation.parquet
      - split: test
        path: metal_ion_binding/test.parquet
  - config_name: peptide
    data_files:
      - split: train
        path: peptide/train.parquet
      - split: validation
        path: peptide/validation.parquet
      - split: test
        path: peptide/test.parquet
  - config_name: phosphorylation
    data_files:
      - split: train
        path: phosphorylation/train.parquet
      - split: validation
        path: phosphorylation/validation.parquet
      - split: test
        path: phosphorylation/test.parquet
  - config_name: post_translational_modification
    data_files:
      - split: train
        path: post_translational_modification/train.parquet
      - split: validation
        path: post_translational_modification/validation.parquet
      - split: test
        path: post_translational_modification/test.parquet
  - config_name: prot_param
    data_files:
      - split: train
        path: prot_param/train.parquet
      - split: validation
        path: prot_param/validation.parquet
      - split: test
        path: prot_param/test.parquet
  - config_name: secondary_structure
    data_files:
      - split: train
        path: secondary_structure/train.parquet
      - split: validation
        path: secondary_structure/validation.parquet
      - split: test
        path: secondary_structure/test.parquet
  - config_name: ssp_q3
    data_files:
      - split: train
        path: ssp_q3/train.parquet
      - split: validation
        path: ssp_q3/validation.parquet
      - split: test
        path: ssp_q3/test.parquet
  - config_name: ssp_q8
    data_files:
      - split: train
        path: ssp_q8/train.parquet
      - split: validation
        path: ssp_q8/validation.parquet
      - split: test
        path: ssp_q8/test.parquet
  - config_name: topology
    data_files:
      - split: train
        path: topology/train.parquet
      - split: validation
        path: topology/validation.parquet
      - split: test
        path: topology/test.parquet

Protein concept probing

Twenty-two protein annotation tasks for probing what a protein language model's internal states encode, from amino-acid composition to Gene Ontology terms. Thirteen tasks label a whole protein and nine label each residue. The human tasks are reviewed Homo sapiens UniProtKB entries shorter than 1,024 residues; four further tasks are xTrimoPGLM benchmark tables.

Config Level Task Proteins Labels Train / validation / test
functional_sites residue multiclass 6,893 6 4,778 / 1,106 / 1,009
go_bp protein multilabel 12,255 304 8,591 / 1,888 / 1,776
go_cc protein multilabel 16,443 164 11,409 / 2,457 / 2,577
go_mf protein multilabel 11,504 123 8,010 / 1,786 / 1,708
interpro_active_site protein multilabel 718 58 482 / 116 / 120
interpro_binding_site protein multilabel 640 39 446 / 87 / 107
interpro_conserved_site protein multilabel 2,948 334 2,062 / 450 / 436
interpro_domain protein multilabel 8,003 364 5,307 / 1,371 / 1,325
interpro_family protein multilabel 3,601 239 2,097 / 678 / 826
interpro_homologous_superfamily protein multilabel 8,198 100 5,499 / 1,368 / 1,331
interpro_repeat protein multilabel 1,189 65 819 / 189 / 181
lipidation residue multiclass 978 25 654 / 129 / 195
localization protein multiclass 7,530 10 5,321 / 590 / 1,619
metal_ion_binding protein binary 7,242 1 5,346 / 599 / 1,297
peptide residue multiclass 4,977 4 3,485 / 700 / 792
phosphorylation residue multiclass 8,648 6 6,057 / 1,304 / 1,287
post_translational_modification residue multiclass 15,349 12 10,722 / 2,400 / 2,227
prot_param protein regression 18,126 31 12,747 / 2,777 / 2,602
secondary_structure residue multiclass 8,986 4 6,310 / 1,351 / 1,325
ssp_q3 residue multiclass 11,479 3 9,731 / 1,083 / 665
ssp_q8 residue multiclass 11,479 8 9,731 / 1,083 / 665
topology residue multiclass 4,777 17 3,378 / 754 / 645

Homology leakage

The human tasks keep their published cluster splits: MMseqs2 clusters at 20% identity (30% for InterPro active site, binding site, conserved site and repeat) are assigned whole to train plus validation or to test, and validation clusters are drawn at 50% identity from the rest, with 80% coverage of the target sequence. The four benchmark tasks keep their published test split, and validation is a random 10% of their train split, so they hold no homology guarantee between train and validation.

How it was built

  1. Read each curated human table and its recorded train, validation and test assignment.
  2. Turn its targets into one label column: a multi-hot vector over the InterPro entries or Gene Ontology terms, 31 ProtParam values, or one class index per residue in the contiguous order of the classes the table holds.
  3. For Gene Ontology, keep the terms with more than six positive proteins in both validation and test.
  4. For the four benchmark tables, split 10% of train off as validation with seed 184502, then drop sequences of 1,024 residues or more.

Columns

Column Meaning
id UniProt accession for the human tasks; a stable sequence-derived id for the benchmark tasks
sequence amino-acid sequence
label multi-hot list (multilabel), list of 31 floats (regression), integer (binary or multiclass), or one integer per residue (residue tasks)

Each config folder also holds metadata.json with the task level, task type and label names. The benchmark tables publish their classes but not the order of their integers, so their label names are class_<n>.

What a model trained on it may say

These are probing benchmarks. InterPro entries and many UniProt features are curated with computational evidence, so a probe here measures agreement with the annotations, not experimentally measured function. Residue tasks count unannotated residues as their own class (-), which dominates most of them.

Sources and licence

The human tasks are the curated tables of Figshare record 10.6084/m9.figshare.31169506, released under CC BY 4.0, built from UniProtKB (accessed 2025-09-09) and the InterPro entry list (accessed 2025-09-16). The four benchmark tasks (metal_ion_binding, localization, ssp_q3, ssp_q8) are from biomap-research on Hugging Face under Apache 2.0.

Files

<config>/train.parquet, <config>/validation.parquet, <config>/test.parquet and <config>/metadata.json for each of the 22 configs.