KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction | Paper Citation Record

Observation ea27c1ee-6fd6-4ab0-8fbc-e7b72bb0572c · outbound

This paper cites On the frustration to predict binding affinities from protein–ligand structures with deep neural networks,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction On the frustration to predict binding affinities from protein–ligand structures with deep neural networks,

Reference 1

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Observation d46094eb-cde1-49df-ba71-dc810fef6fa8 · outbound

This paper cites Computational approaches stream- lining drug discovery,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Computational approaches stream- lining drug discovery,

Reference 2

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This paper cites A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:44:01.250707Z

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This paper cites Deep learning in drug design: protein-ligand binding affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Deep learning in drug design: protein-ligand binding affinity prediction,

Reference 4

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Observation 9afac0e8-6053-4bed-a2fc-eaac0397ed70 · outbound

This paper cites Dyscore: a boosting scoring method with dynamic properties for identifying true binders and nonbinders in structure-based drug discovery,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Dyscore: a boosting scoring method with dynamic properties for identifying true binders and nonbinders in structure-based drug discovery,

Reference 5

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Observation fdf23811-f1d5-4804-8d0e-6c8b5d2e424f · outbound

This paper cites Knowledge-enhanced and structure- enhanced representation learning for protein-ligand binding affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Knowledge-enhanced and structure- enhanced representation learning for protein-ligand binding affinity prediction,

Reference 6

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Observation 34dda440-4bf0-47c1-965b-13f2d30828bc · outbound

This paper cites Interformer: an interaction-aware model for protein-ligand docking and affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Interformer: an interaction-aware model for protein-ligand docking and affinity prediction,

Reference 7

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This paper cites Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules,

Reference 8

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Observation 94498e81-2ba1-4872-abad-86bb6c5a2dca · outbound

This paper cites Deepdta: deep drug–target binding affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Deepdta: deep drug–target binding affinity prediction,

Reference 9

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Observation 665b1082-b54c-46de-8762-9e256f5d184e · outbound

This paper cites Deepconv-dti: Prediction of drug-target interactions via deep learning with convolution on protein sequences,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Deepconv-dti: Prediction of drug-target interactions via deep learning with convolution on protein sequences,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:59.285837Z

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Observation 0232caea-8cd4-4076-904a-2cbc2ad50104 · outbound

This paper cites Drug–target affinity prediction using graph neural network and contact maps,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Drug–target affinity prediction using graph neural network and contact maps,

Reference 11

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Observation 11e59b5b-bd35-40e0-90e2-fcf3a6a26d2a · outbound

This paper cites Mgraphdta: deep multiscale graph neural network for explainable drug–target binding affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Mgraphdta: deep multiscale graph neural network for explainable drug–target binding affinity prediction,

Reference 12

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This paper cites Attention is all you need,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Attention is all you need,

Reference 13

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This paper cites Transformercpi: improving compound– protein interaction prediction by sequence-based deep learning with self- attention mechanism and label reversal experiments,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Transformercpi: improving compound– protein interaction prediction by sequence-based deep learning with self- attention mechanism and label reversal experiments,

Reference 14

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Observation 0e5a6bdf-58f6-4a18-af88-b47533271d18 · outbound

This paper cites Moltrans: molecular interaction transformer for drug–target interaction prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Moltrans: molecular interaction transformer for drug–target interaction prediction,

Reference 15

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Observation cc4735c9-fc7e-4833-9124-23e149c95a30 · outbound

This paper cites Gene ontology: tool for the unification of biology,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Gene ontology: tool for the unification of biology,

Reference 16

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Observation 955b8a40-e98e-4704-91ed-e87b45cc6f73 · outbound

This paper cites A unified drug–target interaction prediction framework based on knowledge graph and recommendation system,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction A unified drug–target interaction prediction framework based on knowledge graph and recommendation system,

Reference 17

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Observation 982f6d9f-8a76-46ef-a62a-504a6b12a84e · outbound

This paper cites Knowledge graph embed- ding: A survey of approaches and applications,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Knowledge graph embed- ding: A survey of approaches and applications,

Reference 18

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This paper cites Evolutionary-scale prediction of atomic- level protein structure with a language model,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Evolutionary-scale prediction of atomic- level protein structure with a language model,

Reference 19

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Observation 9def075c-b4b2-4bf7-a7d2-79939ef8e9f0 · outbound

This paper cites Learning characteristics of graph neural networks predicting protein–ligand affinities,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Learning characteristics of graph neural networks predicting protein–ligand affinities,

Reference 20

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Observation 67fb900f-de51-4db8-9f0e-4e7152619351 · outbound

This paper cites Cross attention network for few-shot classification,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Cross attention network for few-shot classification,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:56.511271Z

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Observation 58dd9bd7-6603-49d4-81fb-4511fb0857eb · outbound

This paper cites A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking,

Reference 22

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This paper cites Graphdta: predicting drug–target binding affinity with graph neural networks,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Graphdta: predicting drug–target binding affinity with graph neural networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:56.089349Z

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Observation 9062984a-2182-4dfa-9160-9dcd243faf8d · outbound

This paper cites Interpretable bilinear atten- tion network with domain adaptation improves drug–target prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Interpretable bilinear atten- tion network with domain adaptation improves drug–target prediction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:55.832800Z

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Observation 4b91b00e-ef1d-4bf3-bbfc-71f27f9f0c32 · outbound

This paper cites Onionnet: a multiple-layer intermolecular- contact-based convolutional neural network for protein–ligand binding affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Onionnet: a multiple-layer intermolecular- contact-based convolutional neural network for protein–ligand binding affinity prediction,

Reference 25

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This paper cites Predicting drug–target interaction using a novel graph neural network with 3d structure-embedded graph representation,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Predicting drug–target interaction using a novel graph neural network with 3d structure-embedded graph representation,

Reference 26

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This paper cites Analyzing learned molecular representations for property prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Analyzing learned molecular representations for property prediction,

Reference 27

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This paper cites Development and evaluation of a deep learning model for protein– ligand binding affinity prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Development and evaluation of a deep learning model for protein– ligand binding affinity prediction,

Reference 28

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Observation 6adc0ef4-8caa-46dd-b327-6ef6bd672730 · outbound

This paper cites Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity,

Reference 29

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Observation d114ba17-329a-4054-bab9-f79ad9be7b97 · outbound

This paper cites Giant: Protein-ligand binding affinity prediction via geometry- aware interactive graph neural network,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Giant: Protein-ligand binding affinity prediction via geometry- aware interactive graph neural network,

Reference 30

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Observation fd4c6c6a-705e-4cf4-bc29-035c44085945 · outbound

This paper cites Biomedical knowledge graph embedding with capsule network for multi-label drug-drug interaction prediction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Biomedical knowledge graph embedding with capsule network for multi-label drug-drug interaction prediction,

Reference 31

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Observation 962992f6-33bb-46e0-9d71-a2a631416430 · outbound

This paper cites Kg-mtl: knowledge graph enhanced multi-task learning for molecular interaction,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Kg-mtl: knowledge graph enhanced multi-task learning for molecular interaction,

Reference 32

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Observation 80b8ef34-9714-4dfe-b4f8-fc7202a1cbe7 · outbound

This paper cites Dgl-lifesci: An open-source toolkit for deep learning on graphs in life science,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Dgl-lifesci: An open-source toolkit for deep learning on graphs in life science,

Reference 33

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Observation 2dae84a9-b904-4a55-95ba-58a0b8c83fcd · outbound

This paper cites Translating embeddings for modeling multi-relational data,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Translating embeddings for modeling multi-relational data,

Reference 34

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This paper cites Rotate: Knowledge graph embedding by relational rotation in complex space,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Rotate: Knowledge graph embedding by relational rotation in complex space,

Reference 35

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This paper cites Adam: A method for stochastic optimization,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Adam: A method for stochastic optimization,

Reference 36

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This paper cites Pdb-wide collection of binding data: current status of the pdbbind database,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Pdb-wide collection of binding data: current status of the pdbbind database,

Reference 37

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This paper cites Csar benchmark exercise of 2010: combined evaluation across all submitted scoring functions,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Csar benchmark exercise of 2010: combined evaluation across all submitted scoring functions,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:52.634678Z

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This paper cites Spatial graph convolutional networks,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Spatial graph convolutional networks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:52.469651Z

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Observation a1c74a9c-d49f-42dd-a982-d564bcbc96f1 · outbound

This paper cites Representing long-range context for graph neural networks with global attention,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Representing long-range context for graph neural networks with global attention,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:52.188987Z

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This paper cites Non-local graph neural networks,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Non-local graph neural networks,

Reference 41

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This paper cites Molecule Attention Transformer.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Molecule Attention Transformer

Reference 42

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This paper cites Directional message passing for molecular graphs,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Directional message passing for molecular graphs,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:51.614616Z

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Observation 64b66aa8-88f2-4bc9-906a-73002fcaca19 · outbound

This paper cites Com- municative representation learning on attributed molecular graphs,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Com- municative representation learning on attributed molecular graphs,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:51.310914Z

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Observation 84453d21-9812-4db7-b401-f97db003800b · outbound

This paper cites Compound–protein interaction prediction with end-to-end learning of neural networks for graphs and sequences,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Compound–protein interaction prediction with end-to-end learning of neural networks for graphs and sequences,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:51.077692Z

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Observation a9876809-3343-485a-9416-b9d94f5d2db3 · outbound

This paper cites The protein data bank,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction The protein data bank,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:50.838088Z

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Observation a4599613-c618-44e2-9cab-80aeb8bce698 · outbound

This paper cites Protein x-ray crystallography and drug discovery,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Protein x-ray crystallography and drug discovery,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:50.566758Z

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Observation f27718c3-6fe6-47c8-bf02-e8cda5a22b41 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Accurate structure prediction of biomolecular interactions with alphafold 3,

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1c069dd-909a-4e9b-95de-e1f882d72aef · outbound

This paper cites Survey: Functional module detection from protein-protein interaction networks,.

KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction Survey: Functional module detection from protein-protein interaction networks,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:43:50.355731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers