Protocol

HuRI PPI link prediction, Accuracy (Table 6)

Evidence concern: excluded from comparisons

The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6

PPI link prediction on HuRI with protein embeddings as GNN node features; Accuracy as printed in Table 6.

77 evaluations · 77 results

Overview

An explanatory profile has not yet been reviewed for this record.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

77 recorded evaluations, 77 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.

View coverage and remaining gaps across all benchmarks

Results

Results are available, but no reviewed comparison panel is linked in this release.

All evaluations

77 evaluations · 77 results. Different protocols are not a single leaderboard.

Protocol: HuRI PPI link prediction, Accuracy (Table 6) · Dataset: HuRI PPI graph (embedding study)

Sorted by Accuracy (HuRI PPI link prediction) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	Accuracy (HuRI PPI link prediction)
GCN with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.799 (best in column)
GCN with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.792
NGNN with GCN with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.782
GraphSAGE with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.772
GraphSAGE with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.771
NGNN with GCN with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.77
NGNN with GraphSAGE with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.769
NGNN with GCN combined with SEAL with majority vote across the representations (PPI embeddings study)Evaluation	0.768
NGNN with GraphSAGE with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.767
NGNN with GraphSAGE combined with SEAL with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.762
NGNN with GraphSAGE combined with SEAL with majority vote across the representations (PPI embeddings study)Evaluation	0.761
NGNN with GraphSAGE combined with SEAL with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.761
GCN with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.76
NGNN with GraphSAGE combined with SEAL with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.76
NGNN with GraphSAGE combined with SEAL with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.76
NGNN with GraphSAGE combined with SEAL with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.76
NGNN with GCN combined with SEAL with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.757
NGNN with GraphSAGE combined with SEAL with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.756
NGNN with GraphSAGE combined with SEAL with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.755
NGNN with GraphSAGE combined with SEAL with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.755
NGNN with GCN with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.755
NGNN with GCN combined with SEAL with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.754
NGNN with GraphSAGE with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.754
NGNN with GCN combined with SEAL with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.753
NGNN with GCN combined with SEAL with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.753
NGNN with GCN combined with SEAL with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.753
NGNN with GCN combined with SEAL with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.75
NGNN with GCN combined with SEAL with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.744
NGNN with GraphSAGE combined with SEAL with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.737
NGNN with GCN combined with SEAL with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.737
NGNN with GCN combined with SEAL with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.735
NGNN with GraphSAGE with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.719
NGNN with GCN with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.717
NGNN with GCN with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.716
GCN with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.715
GraphSAGE with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.706
GCN with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.704
GCN with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.702
NGNN with GraphSAGE combined with SEAL with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.701
NGNN with GCN combined with SEAL with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.7
GCN with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.7
MLP on concatenated protein embeddings (protein-only baseline, no network) with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.699
NGNN with GCN with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.685
NGNN with GCN with majority vote across the representations (PPI embeddings study)Evaluation	0.682
GCN with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.675
GCN with majority vote across the representations (PPI embeddings study)Evaluation	0.671
NGNN with GraphSAGE with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.662
GCN with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.65
GraphSAGE with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.648
MLP on concatenated protein embeddings (protein-only baseline, no network) with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.641
GraphSAGE with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.637
NGNN with GCN with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.624
GraphSAGE with majority vote across the representations (PPI embeddings study)Evaluation	0.622
NGNN with GraphSAGE with majority vote across the representations (PPI embeddings study)Evaluation	0.619
MLP on concatenated protein embeddings (protein-only baseline, no network) with majority vote across the representations (PPI embeddings study)Evaluation	0.617
MLP on concatenated protein embeddings (protein-only baseline, no network) with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.609
MLP on concatenated protein embeddings (protein-only baseline, no network) with randomly initialised node features (baseline) (PPI embeddings study)Evaluation	0.603
NGNN with GCN with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.6
MLP on concatenated protein embeddings (protein-only baseline, no network) with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.595
MLP on concatenated protein embeddings (protein-only baseline, no network) with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.594
MLP on concatenated protein embeddings (protein-only baseline, no network) with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.591
MLP on concatenated protein embeddings (protein-only baseline, no network) with ESM-IF1 protein embeddings (structure) (PPI embeddings study)Evaluation	0.582
MLP on concatenated protein embeddings (protein-only baseline, no network) with PiFold protein embeddings (structure) (PPI embeddings study)Evaluation	0.581
MLP on concatenated protein embeddings (protein-only baseline, no network) with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.571
NGNN with GraphSAGE with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.568
NGNN with GCN with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.568
NGNN with GraphSAGE with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.557
GraphSAGE with ProtTrans protein embeddings (sequence) (PPI embeddings study)Evaluation	0.557
NGNN with GraphSAGE with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.555
GraphSAGE with ProGen2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.549
NGNN with GraphSAGE with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.546
GraphSAGE with ESM-2 protein embeddings (sequence) (PPI embeddings study)Evaluation	0.542
GraphSAGE with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.542
NGNN with GraphSAGE with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.535
NGNN with GCN with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.532
GraphSAGE with ProstT5 protein embeddings (structure) (PPI embeddings study)Evaluation	0.529
GCN with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)Evaluation	0.515

All 77 result rows with coverage, uncertainty and sources

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: GCN with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.792 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / ComplEx on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'ComplEx'
Configuration: GCN with majority vote across the representations (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.671 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / Ensemble on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'Ensemble'
Configuration: GCN with ESM-2 protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.702 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / ESM-2 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'ESM-2'
Configuration: GCN with ESM-IF1 protein embeddings (structure) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.76 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / ESM-IF1 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'ESM-IF1'
Configuration: GCN with PiFold protein embeddings (structure) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.704 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / PiFold on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'PiFold'
Configuration: GCN with ProGen2 protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.715 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / ProGen2 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'ProGen2'
Configuration: GCN with ProstT5 protein embeddings (structure) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.65 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / ProstT5 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'ProstT5'
Configuration: GCN with ProtTrans protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.675 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / ProtTrans on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'ProtTrans'
Configuration: GCN with randomly initialised node features (baseline) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.7 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / Random on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'Random'
Configuration: GCN with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.799 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / RDF2Vec on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'RDF2Vec'
Configuration: GCN with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.515 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GCN / TransE on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GCN', column 'TransE'
Configuration: GraphSAGE with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.772 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / ComplEx on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'ComplEx'
Configuration: GraphSAGE with majority vote across the representations (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.622 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / Ensemble on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'Ensemble'
Configuration: GraphSAGE with ESM-2 protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.542 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / ESM-2 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'ESM-2'
Configuration: GraphSAGE with ESM-IF1 protein embeddings (structure) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.706 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / ESM-IF1 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'ESM-IF1'
Configuration: GraphSAGE with PiFold protein embeddings (structure) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.648 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / PiFold on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'PiFold'
Configuration: GraphSAGE with ProGen2 protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.549 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / ProGen2 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'ProGen2'
Configuration: GraphSAGE with ProstT5 protein embeddings (structure) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.529 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / ProstT5 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'ProstT5'
Configuration: GraphSAGE with ProtTrans protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.557 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / ProtTrans on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'ProtTrans'
Configuration: GraphSAGE with randomly initialised node features (baseline) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.637 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / Random on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'Random'
Configuration: GraphSAGE with RDF2Vec protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.771 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / RDF2Vec on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'RDF2Vec'
Configuration: GraphSAGE with TransE protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.542 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source GraphSAGE / TransE on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'GS', column 'TransE'
Configuration: MLP on concatenated protein embeddings (protein-only baseline, no network) with ComplEx protein embeddings (function (knowledge-graph embedding)) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.641 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source MLP on concatenated protein embeddings (protein-only baseline, no network) / ComplEx on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'MLP', column 'ComplEx'
Configuration: MLP on concatenated protein embeddings (protein-only baseline, no network) with majority vote across the representations (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.617 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source MLP on concatenated protein embeddings (protein-only baseline, no network) / Ensemble on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'MLP', column 'Ensemble'
Configuration: MLP on concatenated protein embeddings (protein-only baseline, no network) with ESM-2 protein embeddings (sequence) (PPI embeddings study)	Protocol: HuRI PPI link prediction, Accuracy (Table 6) Dataset: HuRI PPI graph (embedding study)	0.571 Accuracy (HuRI PPI link prediction) fraction · higher Uncertainty: Not reported by the source: Only a table-wide maximum SD is printed (Table 5/6 footnote) Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons The text's summary does not match the tables: it lists ProtT5 among structure embeddings while the tables print ProstT5; it reports a GraphSAGE with DistMult result (+38% Hits@100 on HuRI) although DistMult is not a column; and the stated gains (for example ESM-2 with GraphSAGE +6% Hits@100 on OGBl-ppa) cannot be reproduced from the printed table values (GS random 0.0104, ESM-2 0.2421). Values are kept as printed; comparisons should rely on the tables only after a reviewer has judged this. Random-feature baselines on OGBl-ppa (GCN 0.0588, GS 0.0104 Hits@100) look far below the public OGB leaderboard values the authors say they reproduced (Supplementary Table S2, not retrieved; reviewer did not verify the leaderboard values).The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Results and discussion, first paragraph; Tables 5 and 6 Methods, coverage and source MLP on concatenated protein embeddings (protein-only baseline, no network) / ESM-2 on HuRI (Accuracy) lit-interactions-20261011-ppiemb-protocol-huri-accuracy Aggregation: Not reported The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Table 6, block 'HuRI', row 'MLP', column 'ESM-2'

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The role of protein embeddings for protein-protein interaction prediction with graph neural networks · Original source · Briefings in Bioinformatics 2026, bbag313; PMC13280947 full-text XML

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Stable ID: lit-interactions-20261011-ppiemb-protocol-huri-accuracy

areas: molecular-interactions; proteins-complexes
contexts: research
protocol: HuRI PPI link prediction; Accuracy
version: bbag313
metric: accuracy
metric direction: higher
unit: fraction
limitations: The authors ran every configuration; none of the embedding models is theirs.; No per-cell uncertainty or run count is printed; the footnote of Tables 5 and 6 gives only the table-wide maximum standard deviation (0.0711 OGBl-ppa, 0.0928 HuRI).; The MLP row is a protein-only binary classifier on concatenated embeddings, not a GNN.; The text's summary of gains does not match the printed values; see the source's evidence concern.
source locator: Table 6, block 'HuRI'

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assessment: NGNN with GCN combined with SEAL / ComplEx on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / Ensemble on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / ESM-2 on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / ESM-IF1 on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / PiFold on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / ProGen2 on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / ProstT5 on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / ProtTrans on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / Random on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / RDF2Vec on HuRI (Accuracy)
assessment: NGNN with GCN combined with SEAL / TransE on HuRI (Accuracy)
assessment: NGNN with GCN / ProGen2 on HuRI (Accuracy)
assessment: NGNN with GCN / ProstT5 on HuRI (Accuracy)
assessment: NGNN with GCN / ProtTrans on HuRI (Accuracy)
assessment: NGNN with GCN / Random on HuRI (Accuracy)
assessment: NGNN with GCN / RDF2Vec on HuRI (Accuracy)
assessment: NGNN with GCN / TransE on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / ComplEx on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / Ensemble on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / ESM-2 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / ESM-IF1 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / PiFold on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / ComplEx on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / Ensemble on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / ESM-2 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / ESM-IF1 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / PiFold on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / ProGen2 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / ProstT5 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / ProtTrans on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / Random on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / RDF2Vec on HuRI (Accuracy)
assessment: NGNN with GraphSAGE combined with SEAL / TransE on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / ProGen2 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / ProstT5 on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / ProtTrans on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / Random on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / RDF2Vec on HuRI (Accuracy)
assessment: NGNN with GraphSAGE / TransE on HuRI (Accuracy)

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