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Paper Citation Record · LEDGER

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning

As of 7 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2607.24314.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.24314 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T18:33:48.701032Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

69 of 69 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved64
  • parse uncertain0
  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 432ae11c-3413-4ae8-b338-5fa2807a9148 · outbound

This paper cites & Philpott, K.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Philpott, K

Reference 1

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Observation c49b55a4-2340-4ad3-9b1f-6e158b3e9fb1 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 2

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Observation 5e29b4da-463f-41fc-9d36-b70815c244b3 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 3

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Observation 82f9781c-9004-4289-bc53-9ba77d43f6de · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 4

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Observation 3c2e2489-9781-446d-afa6-cf90e983ad94 · outbound

This paper cites & Zhou, S.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Zhou, S

Reference 5

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Observation d5d7102e-d8b7-4750-b9ba-0322d10797f2 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 6

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Observation 8aea5c08-337c-4f63-a9b9-8a014245ed74 · outbound

This paper cites & Houston, J.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Houston, J

Reference 7

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Observation 19e760f2-98c9-4fce-9040-f382e8ea639c · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 8

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Observation 15a7989d-fb6a-4353-ae4b-39d72e802768 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 9

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Observation 8fcbc48c-eacb-4b67-8443-cf320a04c7fe · outbound

This paper cites & Lowe, E.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Lowe, E

Reference 10

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Observation bbaae902-5f84-440c-b8f5-dfebdfa37824 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 11

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Observation c06e52c0-0efa-4350-95f5-a9f6ebd86416 · outbound

This paper cites & Maddi, S.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Maddi, S

Reference 12

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Observation f536e90e-8599-4f0c-a2cf-517c8bc86ec4 · outbound

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MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Vaid, R

Reference 13

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verified exact
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7120e1e9-c0b9-4833-b3a8-a72c8b86de95 · outbound

This paper cites Neural Message Passing for Quantum Chemistry.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Neural Message Passing for Quantum Chemistry

Reference 14

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Observation f94fe382-c10c-48f4-a36f-c54cdc5bde43 · outbound

This paper cites SchNet: A continuous-filter convolutional neural network for modeling quantum interactions.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Reference 15

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Observation af9cabfa-e686-4e6d-a78e-0d6ba4856359 · outbound

This paper cites Graph-based Molecular Representation Learning.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Graph-based Molecular Representation Learning

Reference 16

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Observation e5904521-2db7-446d-91c2-4d8729610619 · outbound

This paper cites -H., Le, M.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning -H., Le, M

Reference 17

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Observation df115b10-1cb9-4f2a-848e-1ca2dd837919 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 18

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Observation 6aa9c2c0-4c0e-4039-8663-a8f2343b4213 · outbound

This paper cites & Chandrasekaran, S.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Chandrasekaran, S

Reference 19

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Observation ecde72b1-5aef-4346-8d21-803d8c5f6336 · outbound

This paper cites & Xie, L.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Xie, L

Reference 20

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Observation 22536d84-c7c2-4774-8709-6e136ef0bb5a · outbound

This paper cites & Barati Farimani, A.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Barati Farimani, A

Reference 21

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Observation 2d264aec-cf6e-4c6f-af96-a7e6568ecb50 · outbound

This paper cites Graph Contrastive Learning with Augmentations.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Graph Contrastive Learning with Augmentations

Reference 22

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Observation 16766a44-4849-4f68-97f6-92af25f02b90 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 23

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Observation 32a431f0-57d0-400f-aa21-3a9e671db5d8 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 24

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Observation 2d39b457-6a7c-4f5c-9936-96ac80d2240b · outbound

This paper cites Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel

Reference 25

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Observation 3fe4818e-521c-4305-afb6-28bf0aad2c93 · outbound

This paper cites Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond

Reference 26

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Observation 70741d5e-d10d-4258-a039-8dc09e6fc85e · outbound

This paper cites & Zhou, S.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Zhou, S

Reference 27

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Observation 0ca40d80-f76c-460e-9e2a-9beabc68cab8 · outbound

This paper cites Concepts and applications of molecular similarity, by Mark A.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Concepts and applications of molecular similarity, by Mark A

Reference 28

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Observation 88df222b-bec2-4e37-85d4-ce6686551e56 · outbound

This paper cites & Ramsundar, B.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Ramsundar, B

Reference 29

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Observation 64791012-9a76-46e6-a786-4c9e73e8d592 · outbound

This paper cites DeepGCNs: Can GCNs Go as Deep as CNNs?.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 30

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Observation 328a0e60-93c1-4610-b2b4-dc874907bb7b · outbound

This paper cites & Liu, X.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Liu, X

Reference 31

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Observation 2538e910-5ef7-46ff-a897-2f72d4d42508 · outbound

This paper cites -H., Liu, Z.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning -H., Liu, Z

Reference 32

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Observation cdcb30ad-d620-43ca-903e-dedfcfa27cb4 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 33

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Observation 27034b93-bed4-48be-8b48-981093e802d7 · outbound

This paper cites Graph Foundation Models: Concepts, Opportunities and Challenges.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Graph Foundation Models: Concepts, Opportunities and Challenges

Reference 34

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Observation 052a657f-282a-4e30-8149-ce03e5f4ef01 · outbound

This paper cites MoleculeNet: A Benchmark for Molecular Machine Learning.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning MoleculeNet: A Benchmark for Molecular Machine Learning

Reference 35

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Observation 3c33f5e8-4ca3-4b10-8ce5-fcf4d2101177 · outbound

This paper cites Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective

Reference 36

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Observation 932aa1e5-0ca6-4603-adb1-56e10a9d1aa9 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 37

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Observation 6b3dab5d-5d19-4940-b761-3f4ba06e3397 · outbound

This paper cites A Fair Comparison of Graph Neural Networks for Graph Classification.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning A Fair Comparison of Graph Neural Networks for Graph Classification

Reference 38

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Observation 14ce59e8-3aae-432f-9aa0-45573d2202ac · outbound

This paper cites N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules

Reference 39

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Observation d77ce588-7946-4557-a477-6239178751a8 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 40

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Observation 9513f994-a1ae-471c-bfd8-1a8f39f75927 · outbound

This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 41

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Observation 9aa2040b-667e-4e32-94d2-efc5c0ecd9ba · outbound

This paper cites Random Forests.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Random Forests

Reference 42

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Observation d86c27df-55f7-4a39-84c0-55c209171929 · outbound

This paper cites & Vapnik, V.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Vapnik, V

Reference 43

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Observation 767b2f40-75f0-4906-970f-b78d254a5353 · outbound

This paper cites & Guestrin, C.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Guestrin, C

Reference 44

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Observation 3bc9ee3b-d56d-4685-84ad-f9ecc94b830e · outbound

This paper cites Application of the logistic function to bio -assay.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Application of the logistic function to bio -assay

Reference 45

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Observation 4ea768b6-82cd-4690-94fa-009e74d542f1 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 46

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Observation a0218f74-3078-481f-ac4c-722e7e6e5f82 · outbound

This paper cites PubChem BioAssay: Quantitative High -Through put Screening for Inhibitors of Human Cytochrome P450 Isoforms 1A2, 2C9, 2C19, 2D6, and 3 A4 (AID: 1851).

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning PubChem BioAssay: Quantitative High -Through put Screening for Inhibitors of Human Cytochrome P450 Isoforms 1A2, 2C9, 2C19, 2D6, and 3 A4 (AID: 1851)

Reference 47

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Observation 123ae252-3993-4e32-a7ac-a7cc93f1b8ba · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 48

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Observation 1dbc8857-a462-46e9-9201-a8e9c61caa75 · outbound

This paper cites W., AlRabiah, H., Mostafa, G.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning W., AlRabiah, H., Mostafa, G

Reference 49

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Observation af16095b-fd17-40fc-aabe-743c400b7c94 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 50

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Observation b470bb90-9710-4473-9406-febdbcf09832 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 51

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Observation d6d3c442-0174-46f9-842a-f564e0d6df23 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 52

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Observation ca82c31d-a874-40fe-9cfe-964cb5353374 · outbound

This paper cites B., Mathé , E.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning B., Mathé , E

Reference 53

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Observation b90bcdcc-f4df-4750-9462-6e4150d4facd · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 54

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Observation d3a2e718-d3a8-4cb7-9b0b-2c42072d4ee5 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 55

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Observation 15a91ec1-fbca-497e-8f98-6e2d310eff4f · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 56

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Observation 89cddbfe-6a85-41ca-a959-108442550adf · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Fast Graph Representation Learning with PyTorch Geometric

Reference 57

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Observation b35af8dd-1cd2-4650-945f-e4d2c99b16b4 · outbound

This paper cites Scikit -learn: Machine Learning in Python.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Scikit -learn: Machine Learning in Python

Reference 58

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Observation 915c243b-0d51-44db-9659-1d8c921e9ee3 · outbound

This paper cites & Obach, R.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Obach, R

Reference 59

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Observation 9d7956a4-e87d-4b2a-80ac-e95bf475027a · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 60

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Observation 9ddc6868-4ddf-4f26-839a-d918ad592cdd · outbound

This paper cites & Mahanta, H.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Mahanta, H

Reference 61

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Observation 0fbb5a24-d2df-4da3-91c3-a5f7cfd9e5fe · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 62

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Observation 57625a4a-e071-4e7e-a141-5d19a22b14c2 · outbound

This paper cites & Kalutarage, H.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning & Kalutarage, H

Reference 63

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Observation b98cb981-760c-4909-b828-cd540020d044 · outbound

This paper cites This compound was hermetically sealed, stored away from light at 2 –8 °C, and had a shelf life of 2 years.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning This compound was hermetically sealed, stored away from light at 2 –8 °C, and had a shelf life of 2 years

Reference 64

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Observation 9eedf315-a10c-4f7c-a662-d5527cbe7545 · outbound

This paper cites For Oroxylin A, eight gradient concentrations including 0.1, 0.2, 0.5, 1, 2, 5, 10, and 30 μM were adopted universally for all eight CYP isoforms tested.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning For Oroxylin A, eight gradient concentrations including 0.1, 0.2, 0.5, 1, 2, 5, 10, and 30 μM were adopted universally for all eight CYP isoforms tested

Reference 65

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Observation 826aeaf6-acd6-4a66-a38c-d482250f630c · outbound

This paper cites The metabolic half-life (t) was calculated using the formula t = ln2 / k.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning The metabolic half-life (t) was calculated using the formula t = ln2 / k

Reference 66

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Observation 5be1c010-90bc-4260-95de-37d91c390be8 · outbound

This paper cites an unresolved cited work.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Unresolved cited work

Reference 67

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Observation 65e26da8-0005-446a-9c4e-b763c80db4a4 · outbound

This paper cites Representative column station- ary phases: Agilent Extend-C18 (1.8 μm), Waters ACQUITY BEH C18 (1.7 μm), with matching guard pre-columns.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Representative column station- ary phases: Agilent Extend-C18 (1.8 μm), Waters ACQUITY BEH C18 (1.7 μm), with matching guard pre-columns

Reference 68

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Observation 0ef8747c-602d-4b3c-9e16-f69f35c725cf · outbound

This paper cites Kinetic parameters (k, t1/2, CLint) and IC50 values were reported as mean values of n=3 biological replicates with standard deviation where applicable.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Kinetic parameters (k, t1/2, CLint) and IC50 values were reported as mean values of n=3 biological replicates with standard deviation where applicable

Reference 69

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Pith citing papers

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