CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction | Paper Citation Record

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This paper cites Computer-calculated compounds.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Computer-calculated compounds

Reference 1

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This paper cites Ultra-large library docking for discovering new chemotypes.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Ultra-large library docking for discovering new chemotypes

Reference 2

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This paper cites Docking and scor- ing in virtual screening for drug discovery: methods and applications.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Docking and scor- ing in virtual screening for drug discovery: methods and applications

Reference 3

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This paper cites Molecular docking: shifting paradigms in drug discovery.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Molecular docking: shifting paradigms in drug discovery

Reference 4

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This paper cites Software for molecular dock- ing: a review.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Software for molecular dock- ing: a review

Reference 5

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This paper cites Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field

Reference 6

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This paper cites Computational methods in drug discovery.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Computational methods in drug discovery

Reference 7

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This paper cites Highly accurate protein structure prediction with alphafold.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Highly accurate protein structure prediction with alphafold

Reference 8

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This paper cites Accurate prediction of protein structures and interactions using a three-track neural network.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Accurate prediction of protein structures and interactions using a three-track neural network

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

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Evolutionary-scale prediction of atomic-level protein structure with a language model

Reference 10

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This paper cites Multiobjective tree-based reinforcement learning for estimating tol- erant dynamic treatment regimes.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Multiobjective tree-based reinforcement learning for estimating tol- erant dynamic treatment regimes

Reference 11

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This paper cites Challenges and current status of computational methods for docking small molecules to nucleic acids.European journal of medicinal chemistry , 168:414–425, 2019.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Challenges and current status of computational methods for docking small molecules to nucleic acids.European journal of medicinal chemistry , 168:414–425, 2019

Reference 12

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This paper cites Machine learning in chemoin- formatics and drug discovery.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Machine learning in chemoin- formatics and drug discovery

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This paper cites Scientific Reports, 14(1):7526, 2024.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Scientific Reports, 14(1):7526, 2024

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This paper cites Inactive-enriched machine-learning models exploiting patent data improve structure- based virtual screening for pdl1 dimerizers.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Inactive-enriched machine-learning models exploiting patent data improve structure- based virtual screening for pdl1 dimerizers

Reference 15

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This paper cites Discovery of novel non-steroidal selective glucocorti- coid receptor modulators by structure-and ign-based virtual screening, structural optimization, and biological evaluation.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Discovery of novel non-steroidal selective glucocorti- coid receptor modulators by structure-and ign-based virtual screening, structural optimization, and biological evaluation

Reference 16

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This paper cites Machine learning methods for small data challenges in molecular science.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Machine learning methods for small data challenges in molecular science

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This paper cites A review of machine learning methods for imbalanced data challenges in chemistry.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction A review of machine learning methods for imbalanced data challenges in chemistry

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

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction A machine learning approach to predicting protein– ligand binding affinity with applications to molecular docking

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This paper cites Improving scoring-docking-screening powers of protein– ligand scoring functions using random forest.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Improving scoring-docking-screening powers of protein– ligand scoring functions using random forest

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This paper cites Development of a polynomial scoring function p3-score for improved scoring and ranking powers.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Development of a polynomial scoring function p3-score for improved scoring and ranking powers

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This paper cites A review of mathematical representations of biomolecular data.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction A review of mathematical representations of biomolecular data

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This paper cites Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Mathematical deep learning for pose and binding affinity prediction and ranking in d3r grand challenges

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Persistent spectral graph

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Persistent spectral–based machine learning (perspect ml) for protein-ligand binding affinity prediction

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This paper cites Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Mathdl: mathematical deep learning for d3r grand challenge 4

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This paper cites Combinatorial Commutative Algebra, volume 227 ofGraduate Texts in Mathematics.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Combinatorial Commutative Algebra, volume 227 ofGraduate Texts in Mathematics

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This paper cites Commutative algebra: with a view toward algebraic geometry , volume 150.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Commutative algebra: with a view toward algebraic geometry , volume 150

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Persistent Stanley--Reisner Theory

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Unresolved cited work

Reference 32

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This paper cites Cohen-Macaulay Rings, volume 39 of Cambridge Studies in Advanced Mathematics.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Cohen-Macaulay Rings, volume 39 of Cambridge Studies in Advanced Mathematics

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Monomial ideals, edge ideals of hypergraphs, and their graded betti numbers

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Persistent homology—a survey

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Computing persistent homology

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction TopologyNet: Topology based deep convolutional and multi- task neural networks for biomolecular property predictions

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Position: Topological Deep Learning is the New Frontier for Relational Learning

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

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Pdb-wide collection of binding data: current status of the pdbbind database

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This paper cites Metalprognet: a structure-based deep graph model for metalloprotein–ligand interaction predictions.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Metalprognet: a structure-based deep graph model for metalloprotein–ligand interaction predictions

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CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Persistent path-spectral (pps) based machine learning for protein–ligand binding affinity prediction

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This paper cites Metalloproteomes: a bioinformatic approach.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Metalloproteomes: a bioinformatic approach

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This paper cites Metallomics and the cell: some definitions and general com- ments.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Metallomics and the cell: some definitions and general com- ments

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This paper cites De novo metalloprotein design.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction De novo metalloprotein design

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This paper cites To what extent do structural changes in catalytic metal sites affect enzyme function? Journal of inorganic biochemistry , 179:40–53, 2018.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction To what extent do structural changes in catalytic metal sites affect enzyme function? Journal of inorganic biochemistry , 179:40–53, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.552326Z

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This paper cites Bio-inorganic chemistry, volume 10.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Bio-inorganic chemistry, volume 10

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.541724Z

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Observation 45858b8b-e33f-4aa1-8e73-7cc4fba51b44 · outbound

This paper cites How do bacterial cells ensure that metalloproteins get the correct metal? Nature Reviews Microbiology, 7(1):25–35, 2009.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction How do bacterial cells ensure that metalloproteins get the correct metal? Nature Reviews Microbiology, 7(1):25–35, 2009

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.532902Z

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Observation 60a6dad3-80b7-41a8-869f-03d2325341ef · outbound

This paper cites Join persistent homology (jph)-based machine learning for metalloprotein–ligand binding affinity prediction.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Join persistent homology (jph)-based machine learning for metalloprotein–ligand binding affinity prediction

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Observation 3b7b999c-627d-4cf7-b215-9499e4d442b6 · outbound

This paper cites Rosenet: improving binding affin- ity prediction by leveraging molecular mechanics energies with an ensemble of 3d convolutional neural networks.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Rosenet: improving binding affin- ity prediction by leveraging molecular mechanics energies with an ensemble of 3d convolutional neural networks

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.513218Z

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Observation 5739df46-5ae2-4f81-b417-f1d8b106f15d · outbound

This paper cites Nnscore 2.0: a neural-network receptor–ligand scoring function.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Nnscore 2.0: a neural-network receptor–ligand scoring function

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.503769Z

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Observation 21f2347f-ade5-4616-b2ac-39a9794e289c · outbound

This paper cites an unresolved cited work.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Unresolved cited work

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T10:16:57.416240Z

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Observation 510b3075-0c2b-4ee1-85fe-568fc76f6042 · outbound

This paper cites Extracting predictive representations from hundreds of millions of molecules.The journal of physical chemistry letters, 12(44):10793– 10801, 2021.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction Extracting predictive representations from hundreds of millions of molecules.The journal of physical chemistry letters, 12(44):10793– 10801, 2021

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.487439Z

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Observation 6ccd814d-f19f-438d-bb2f-d721e7f1fe85 · outbound

This paper cites SVSBI: sequence-based virtual screen- ing of biomolecular interactions.

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction SVSBI: sequence-based virtual screen- ing of biomolecular interactions

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:16:57.476769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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