Paper Citation Record · LEDGER

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders

As of 23 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 3 inbound Pith citation observations for arXiv:2506.02051.

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

pith.paper-citation-record.v1
2506.02051 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:00:52.536713Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:24:33.631549Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T13:43:29.130109Z

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation f94d94cf-b31a-474f-8ef0-461a085b1f4c · outbound

This paper cites Trends in kinase drug discovery: targets, indications and inhibitor design.Nature Reviews Drug Discovery, 20(11):839–861,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Trends in kinase drug discovery: targets, indications and inhibitor design.Nature Reviews Drug Discovery, 20(11):839–861,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.976794Z

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Observation 1c13758e-ea68-403d-9f50-fe0f564fffa9 · outbound

This paper cites Application of generative autoencoder in de novo molecular design.Molecular informatics, 37(1- 2):1700123,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Application of generative autoencoder in de novo molecular design.Molecular informatics, 37(1- 2):1700123,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.955173Z

Source-reported events for the cited work

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Observation d0a11444-53b7-445f-972a-83065b0a0b83 · outbound

This paper cites Attention-based generative models for de novo molecular design.Chemical Science, 12(24):8362–8372,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Attention-based generative models for de novo molecular design.Chemical Science, 12(24):8362–8372,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.933943Z

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Observation 448d3c33-f6d1-4831-aefd-367a227bff67 · outbound

This paper cites Automatic chemical design using a data-driven continuous representation of molecules.ACS central science, 4(2):268–276,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Automatic chemical design using a data-driven continuous representation of molecules.ACS central science, 4(2):268–276,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.923441Z

Source-reported events for the cited work

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Observation 26eff800-f38c-4eca-8c5c-79d7bdd1bf1d · outbound

This paper cites Goodfellow, Jean Pouget- Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Goodfellow, Jean Pouget- Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.913049Z

Source-reported events for the cited work

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Observation b7bbb8e6-d24b-48f6-92af-ab0b2193cc69 · outbound

This paper cites Pre- dicting cellular responses to novel drug perturbations at a single-cell resolution.Advances in Neural Information Processing Systems, 35:26711–26722,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Pre- dicting cellular responses to novel drug perturbations at a single-cell resolution.Advances in Neural Information Processing Systems, 35:26711–26722,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.903294Z

Source-reported events for the cited work

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Observation ed72c0ea-3c13-41f9-bcfc-23f1dd2c00b3 · outbound

This paper cites Auto-Encoding Variational Bayes.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Auto-Encoding Variational Bayes

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:00:52.458869Z

Source-reported events for the cited work

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Observation 22874f41-2fbb-4c18-a04a-61a3dde7ffcc · outbound

This paper cites Learning Deep Generative Models of Graphs.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Learning Deep Generative Models of Graphs

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:00:52.465243Z

Source-reported events for the cited work

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Observation 43e6e3e2-759d-42e7-969b-fe9649092e3e · outbound

This paper cites Re- cent advances in therapeutic strategies for triple-negative breast cancer.Journal of hematology & oncology, 15(1):121,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Re- cent advances in therapeutic strategies for triple-negative breast cancer.Journal of hematology & oncology, 15(1):121,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.842564Z

Source-reported events for the cited work

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Observation a100174b-da36-47a2-9829-2d9fe8696381 · outbound

This paper cites Use of artificial intelligence to enhance phenotypic drug discovery.Drug Discovery Today, 26(4):887–901,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Use of artificial intelligence to enhance phenotypic drug discovery.Drug Discovery Today, 26(4):887–901,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.832687Z

Source-reported events for the cited work

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Observation ecd3c3a2-ea66-4af8-971a-9e7223c1b433 · outbound

This paper cites The emerging role of mass spectrometry-based proteomics in drug discovery.Nature Reviews Drug Discovery, 21(9):637–654,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders The emerging role of mass spectrometry-based proteomics in drug discovery.Nature Reviews Drug Discovery, 21(9):637–654,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.822468Z

Source-reported events for the cited work

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Observation 6182ada8-6d7b-4958-a5b6-73572875fd78 · outbound

This paper cites De novo generation of hit-like molecules from gene expression signatures using artificial intelligence.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders De novo generation of hit-like molecules from gene expression signatures using artificial intelligence

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.812271Z

Source-reported events for the cited work

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Observation daae0aa6-789b-498f-b05e-4f954be95dc8 · outbound

This paper cites De novo design of bioac- tive small molecules by artificial intelligence.Molecular informatics, 37(1-2):1700153,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders De novo design of bioac- tive small molecules by artificial intelligence.Molecular informatics, 37(1-2):1700153,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.802199Z

Source-reported events for the cited work

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Observation 5dca636a-ce1e-4938-bd61-af1328d92c57 · outbound

This paper cites Op- portunities and challenges in phenotypic drug discovery: an industry perspective.Nature reviews Drug discovery, 16(8):531–543,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Op- portunities and challenges in phenotypic drug discovery: an industry perspective.Nature reviews Drug discovery, 16(8):531–543,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.792366Z

Source-reported events for the cited work

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Observation e56eac4a-dd54-4943-a651-b3044f2c0dd8 · outbound

This paper cites Fame: fragment-based conditional molecular gen- eration for phenotypic drug discovery.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Fame: fragment-based conditional molecular gen- eration for phenotypic drug discovery

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.770837Z

Source-reported events for the cited work

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Observation 5db3ae93-5a88-425c-a35f-e74b1ed053ab · outbound

This paper cites Deep reinforcement learning for de novo drug design.Science advances, 4(7):eaap7885,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Deep reinforcement learning for de novo drug design.Science advances, 4(7):eaap7885,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.760148Z

Source-reported events for the cited work

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Observation 865fd2ed-bc8c-459b-bd83-a95ec9104154 · outbound

This paper cites off-target.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders off-target

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.750105Z

Source-reported events for the cited work

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Observation ccb75644-5875-4d63-b08b-c874f90a850b · outbound

This paper cites Generating focused molecule libraries for drug discovery with recurrent neural networks.ACS central science, 4(1):120–131,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Generating focused molecule libraries for drug discovery with recurrent neural networks.ACS central science, 4(1):120–131,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.739771Z

Source-reported events for the cited work

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Observation 0d6e96f6-1a5a-4dd7-b410-57ad51ccf7ab · outbound

This paper cites Molecular generation for desired transcriptome changes with adversarial autoencoders.Frontiers in Pharmacol- ogy, 11:269,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Molecular generation for desired transcriptome changes with adversarial autoencoders.Frontiers in Pharmacol- ogy, 11:269,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.730261Z

Source-reported events for the cited work

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Observation e422a6b8-e682-4407-b84b-a1b9fce672c0 · outbound

This paper cites Corsello, and et al.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Corsello, and et al

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.719166Z

Source-reported events for the cited work

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Observation 7e41e275-e4d8-448f-a57a-785fa2cfd54a · outbound

This paper cites How were new medicines discovered?Nature reviews Drug discovery, 10(7):507–519,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders How were new medicines discovered?Nature reviews Drug discovery, 10(7):507–519,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.708971Z

Source-reported events for the cited work

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Observation 3dccae82-8c7e-4105-be32-f1e56cb7289c · outbound

This paper cites Transi- gen: Deep representation learning of chemical-induced transcriptional profile.bioRxiv, pages 2023–11,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Transi- gen: Deep representation learning of chemical-induced transcriptional profile.bioRxiv, pages 2023–11,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.689256Z

Source-reported events for the cited work

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Observation 7f22a50c-48e6-448b-9687-5792acee6586 · outbound

This paper cites Phenotypic drug discovery: recent successes, lessons learned and new directions.Nature Reviews Drug Discovery, 21(12):899–914,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Phenotypic drug discovery: recent successes, lessons learned and new directions.Nature Reviews Drug Discovery, 21(12):899–914,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.678914Z

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Observation a1f09a2c-c32c-48a5-a25e-e8440e15d775 · outbound

This paper cites A Transformer-based Generative Model for De Novo Molecular Design.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders A Transformer-based Generative Model for De Novo Molecular Design

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:00:52.572945Z

Source-reported events for the cited work

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Observation 2bf0412b-6481-4e75-b270-4726aa6ead3c · outbound

This paper cites The cancer genome atlas pan- cancer analysis project.Nature Genetics, 45(10):1113– 1120,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders The cancer genome atlas pan- cancer analysis project.Nature Genetics, 45(10):1113– 1120,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.667930Z

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Observation 1df90848-4e53-49d1-aa2c-b865a5df7668 · outbound

This paper cites Drugbank: a comprehensive resource for in silico drug discovery and exploration.Nucleic acids research, 34(suppl 1):D668– D672,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Drugbank: a comprehensive resource for in silico drug discovery and exploration.Nucleic acids research, 34(suppl 1):D668– D672,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.657691Z

Source-reported events for the cited work

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Observation abfb33fb-e380-49e1-8e85-c2220e2e1c44 · outbound

This paper cites De novo molecule design using molecular generative mod- els constrained by ligand–protein interactions.Journal of chemical information and modeling, 62(14):3291–3306,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders De novo molecule design using molecular generative mod- els constrained by ligand–protein interactions.Journal of chemical information and modeling, 62(14):3291–3306,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.635698Z

Source-reported events for the cited work

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Observation c3bd8212-4dd8-4346-b95e-57b898847006 · outbound

This paper cites Deep learning enables rapid identification of potent ddr1 kinase inhibitors.Nature biotechnology, 37(9):1038–1040, 2019.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Deep learning enables rapid identification of potent ddr1 kinase inhibitors.Nature biotechnology, 37(9):1038–1040, 2019

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.625695Z

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Observation 0f413681-706b-4e5d-8b40-5508d34a87a3 · outbound

This paper cites De novo drug design based on patient gene expression profiles via deep learning.Molecular Informatics, 42(8- 9):2300064,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders De novo drug design based on patient gene expression profiles via deep learning.Molecular Informatics, 42(8- 9):2300064,

Reference 2006

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.646376Z

Source-reported events for the cited work

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Observation 99e1b1f6-eaba-4135-8f87-0332a5414573 · outbound

This paper cites Drug target com- mons: a community effort to build a consensus knowledge base for drug-target interactions.Cell chemical biology, 25(2):224–229,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Drug target com- mons: a community effort to build a consensus knowledge base for drug-target interactions.Cell chemical biology, 25(2):224–229,

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.699241Z

Source-reported events for the cited work

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Observation f39eb167-6e05-4e8f-9ae4-7b4684524df2 · outbound

This paper cites Gxvaes: Two joint vaes generate hit molecules from gene expression profiles.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Gxvaes: Two joint vaes generate hit molecules from gene expression profiles

Reference 2013

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.853423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0736dee6-34a7-496d-bc37-1b5ac3a80f74 · outbound

This paper cites Gex2sgen: designing drug-like molecules from desired gene expression signa- tures.Journal of Chemical Information and Modeling, 63(7):1882–1893,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Gex2sgen: designing drug-like molecules from desired gene expression signa- tures.Journal of Chemical Information and Modeling, 63(7):1882–1893,

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.944350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d38c5802-ac48-4cf0-bccd-8564b08ec867 · outbound

This paper cites De novo generation of multi-target compounds using deep generative chemistry.Nature Communications, 15(1):3636,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders De novo generation of multi-target compounds using deep generative chemistry.Nature Communications, 15(1):3636,

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.781156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3b2a675b-4cab-4ab3-9e87-5bab4fa6455a · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T12:00:52.168335Z

Source-reported events for the cited work

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Observation d2c73e64-feb3-43f6-8b9e-7b39575a47b7 · outbound

This paper cites Triomphe: transcriptome-based inference and generation of molecules with desired phenotypes by machine learning.Journal of Chemical Information and Modeling, 61(9):4303–4320,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Triomphe: transcriptome-based inference and generation of molecules with desired phenotypes by machine learning.Journal of Chemical Information and Modeling, 61(9):4303–4320,

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.865143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 89ee076e-48a7-45e9-8c1f-2136b8ef3c8a · outbound

This paper cites The future of phenotypic drug discovery.Cell chemical biology, 28(3):424–430,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders The future of phenotypic drug discovery.Cell chemical biology, 28(3):424–430,

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.966068Z

Source-reported events for the cited work

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Observation aa6e58c9-5785-4e05-807f-835967d61e87 · outbound

This paper cites Predict- ing single-cell cellular responses to perturbations using cycle consistency learning.Bioinformatics, 40(Supple- ment 1):i462–i470,.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Predict- ing single-cell cellular responses to perturbations using cycle consistency learning.Bioinformatics, 40(Supple- ment 1):i462–i470,

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.893152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6e7d0b8c-43e3-44a3-a137-a78c060f9460 · outbound

This paper cites MolGAN: An implicit generative model for small molecular graphs.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders MolGAN: An implicit generative model for small molecular graphs

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T12:00:52.257769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb216ad6-2bb8-499f-83b2-2a58b355ee83 · outbound

This paper cites Hierarchical generation of molecular graphs us- ing structural motifs.

Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders Hierarchical generation of molecular graphs us- ing structural motifs

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:00:52.879800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 4250959a-8cc1-4a7a-94cf-5297750b8bd2 · inbound

Valid Property-Enhanced Contrastive Learning for Targeted Optimization & Resampling for Novel Drug Design cites this paper.

Valid Property-Enhanced Contrastive Learning for Targeted Optimization & Resampling for Novel Drug Design Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T13:24:33.631549Z

Source-reported events for the cited work

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Observation 77e7d79d-43ae-4ff5-ab3d-29de39977321 · inbound

Bridging the phenotype-target gap for molecular generation via multi-objective reinforcement learning cites this paper.

Bridging the phenotype-target gap for molecular generation via multi-objective reinforcement learning Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:21:28.447386Z

Source-reported events for the cited work

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Observation 3b0c46ca-d48b-4e8a-a6ed-c29a8d5c38cc · inbound

PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion cites this paper.

PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion Phenotypic Profile-Informed Generation of Drug-Like Molecules via Dual-Channel Variational Autoencoders

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:43:29.132196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.