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

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

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

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

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

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

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

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

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

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

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

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

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

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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

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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

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

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

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

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

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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

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

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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

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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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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

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

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

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

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

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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)

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

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

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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

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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

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

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

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

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

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

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

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-31T18:33:48.069886Z

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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

Resolution: unresolved; no resolver link, observed 2026-07-31T18:33:48.144711Z

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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

Resolution: unresolved; no resolver link, observed 2026-07-31T18:33:48.149307Z

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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

Resolution: unresolved; no resolver link, observed 2026-07-31T18:33:48.222291Z

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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

Resolution: unresolved; no resolver link, observed 2026-07-31T18:33:48.367759Z

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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

Resolution: unresolved; no resolver link, observed 2026-07-31T18:33:48.653735Z

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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

Resolution: malformed identifier; no resolver link, observed 2026-07-31T18:33:48.701032Z

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