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protein-protein binding-site prediction

This paper-specific evaluation tests protein-protein binding-site prediction using Dset_448.

1 evaluations · 1 metric rows

At a glance

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.

Data, procedure and scoring
PropertyDescription and evidence
Record typePaper-specific task; protocol incompletely extractedLearning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column
InputsDset_448Learning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column
AssessmentAUROCLearning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column
Recorded split or evaluation settingUnextractedLearning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column
DatasetsNot extracted or verified for this record.
OrganismsNot extracted or verified for this record.
AssaysNot extracted or verified for this record.
AdaptationNot extracted or verified for this record.
BaselinesNot extracted or verified for this record.

How it works

Reported evaluation outline

Outline of the existing paper extraction. Split membership, fitting details and scorer implementation remain incompletely reviewed.

Reported evaluation outlineDset_448. Then: Recorded fitting or scoring procedure. Then: Assess AUROCDset_448Recorded fitting or scoringprocedureAssess AUROC
Read the diagram as text
  1. Dset_448
  2. Recorded fitting or scoring procedure
  3. Assess AUROC
Learning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column

Evaluation context

The existing paper extraction describes: Explainable ensemble binding-site predictor using ProtT5 features. This description is retained with the exact evaluation records; it is not a new protocol reconstruction.

Learning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column

Tested models and results

Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
ProtT5 embeddings + ensemble classifier: protein-protein binding-site prediction

Explainable ensemble binding-site predictor using ProtT5 features

Author-reported evaluation · Evaluation metadata: needs review

0.810 AUROC

Unit: fraction · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedLearning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning · Table 2, Dset_448 section, ProtT5 row, AUROC column

Source checking is not independent reproduction.

Strengths and limitations

Profile review details

Catalogue extraction inspected; protocol claims remain limited to the cited evidence. Missing details are not presumed absent from the original paper.

Stable record: reported-task-f0ed5188dbb6d4

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: needs review

Download this release
Technical metadata and extraction receipts

Stable ID: reported-task-f0ed5188dbb6d4

areas
proteins-complexes
tasks
protein-protein binding-site prediction
entity level
task
version
Not reported
task
protein-protein binding-site prediction
scope note
Paper-specific evaluation task; protocol completeness requires further extraction.
missing metadata
protocol version: not_reported_in_legacy_extract; split: not_reported_in_legacy_extract
Related records

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