Paper Citation Record · LEDGER

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning

As of 19 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:1908.07209.

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

pith.paper-citation-record.v1
1908.07209 v4

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:26:50.347920Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

41 of 41 outbound references displayed

verified exact2
verified fuzzy29
unresolved8
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99d51617-d2c3-4b4f-bf73-dd71acf14976 · outbound

This paper cites Computational Exploration of Molecular Scaffolds in Medicinal Chemistry.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Computational Exploration of Molecular Scaffolds in Medicinal Chemistry

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.131990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38a13a73-ea8f-4e9b-b805-3bea9d8a33ad · outbound

This paper cites W.; Murcko, M.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning W.; Murcko, M

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.116850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4a57eb3e-1192-451d-90bf-6d13111b3898 · outbound

This paper cites an unresolved cited work.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Unresolved cited work

Reference 3

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Observation c36410a9-597a-4d67-8799-a4f0b069d301 · outbound

This paper cites Mining for bioactive scaffolds with scaffold networks: improved compound set enrichment from primary screening data.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Mining for bioactive scaffolds with scaffold networks: improved compound set enrichment from primary screening data

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.087673Z

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Observation 552dce15-bbce-4a4f-9f12-a50efd9e2a7e · outbound

This paper cites Identification of Bioactive Scaffolds Based on QSAR Models.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Identification of Bioactive Scaffolds Based on QSAR Models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.072682Z

Source-reported events for the cited work

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Observation 36c72cb6-f7cf-49b1-9b36-3c5369719fd8 · outbound

This paper cites N.; Zhang, J.-H.; Raman, P.; Ertl, P.; Schuffenhauer, A.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning N.; Zhang, J.-H.; Raman, P.; Ertl, P.; Schuffenhauer, A

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.056020Z

Source-reported events for the cited work

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Observation 3fe11681-7010-4765-8a92-c6b5f483d9eb · outbound

This paper cites J.; Janes, J.; Su, A.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning J.; Janes, J.; Su, A

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.041134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f5fe52e6-330c-4b53-9033-2928a352bc6a · outbound

This paper cites A.; Schuffenhauer, A.; Scheck, M.; Wetzel, S.; Casaulta, M.; Odermatt, A.; Ertl, P.; Waldmann, H.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning A.; Schuffenhauer, A.; Scheck, M.; Wetzel, S.; Casaulta, M.; Odermatt, A.; Ertl, P.; Waldmann, H

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.026561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation acde0b19-78c1-44c8-b909-4b9fa3f43069 · outbound

This paper cites A.; Waldmann, H.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning A.; Waldmann, H

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:51.011726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4bfa81e5-7b9b-4672-91c6-7783d9fa7c80 · outbound

This paper cites Scaffold Hunter: a comprehensive visual analytics framework for drug discovery.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Scaffold Hunter: a comprehensive visual analytics framework for drug discovery

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.997139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49945360-e38c-4218-a72e-202304281e5d · outbound

This paper cites Deep learning.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Deep learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.981550Z

Source-reported events for the cited work

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Observation a4aa361b-e34f-4045-8c95-819c917e8c99 · outbound

This paper cites an unresolved cited work.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:26:50.967584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9c37dddf-b0c2-40f6-af64-af88a9a88dac · outbound

This paper cites Computer-based de novo design of drug-like molecules.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Computer-based de novo design of drug-like molecules

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.953544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1dcbb9e0-418b-4694-8ca3-7f2659af701d · outbound

This paper cites an unresolved cited work.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:26:50.939439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 46fbc3ef-a0f9-4f7b-9173-4a95fcb6748f · outbound

This paper cites N.; Duvenaud, D.; Hernandez-Lobato, J.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning N.; Duvenaud, D.; Hernandez-Lobato, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.925498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7af2808c-d281-4b43-8a3c-6f2e669a552e · outbound

This paper cites Molecular de-novo design through deep reinforcement learning.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Molecular de-novo design through deep reinforcement learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.910897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 378395f4-854f-4195-868b-263647d65553 · outbound

This paper cites SMILES, a chemical language and information system.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning SMILES, a chemical language and information system

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.896448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6eda960a-c95c-4fe3-a1f5-70dfbc2a9e28 · outbound

This paper cites Multi-objective de novo drug design with conditional graph generative model.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Multi-objective de novo drug design with conditional graph generative model

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.881317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 20c0a26a-8699-49a7-8637-6181e3f14c83 · outbound

This paper cites Generative Adversarial Nets from a Density Ratio Estimation Perspective.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Generative Adversarial Nets from a Density Ratio Estimation Perspective

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b9648bb4-3c4c-4a24-b76f-a2e6f5d62ff2 · outbound

This paper cites Learning Deep Generative Models of Graphs.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Learning Deep Generative Models of Graphs

Reference 20

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Source-reported events for the cited work

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Observation 7ba1cd20-826e-4f49-9daf-4c065c182e57 · outbound

This paper cites L.; Leskovec, J.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning L.; Leskovec, J

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.866628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d2c89e71-1dc6-43b3-808b-60d29f69ed59 · outbound

This paper cites Junction Tree Variational Autoencoder for Molecular Graph Generation.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Junction Tree Variational Autoencoder for Molecular Graph Generation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.852326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 144c35f1-e0b3-4faf-a307-6592f14212c9 · outbound

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

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning MolGAN: An implicit generative model for small molecular graphs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T12:26:50.262302Z

Source-reported events for the cited work

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Observation 3206e465-7863-41e1-8b77-6d55c6eeb59c · outbound

This paper cites Latent Molecular Optimization for Targeted Therapeutic Design.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Latent Molecular Optimization for Targeted Therapeutic Design

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T12:26:50.267425Z

Source-reported events for the cited work

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Observation e2ceb958-66b6-46da-beb7-ff43ad4a8943 · outbound

This paper cites QBMG: quasi-biogenic molecule generator with deep recurrent neural network.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning QBMG: quasi-biogenic molecule generator with deep recurrent neural network

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.837681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation edd6e24b-ee04-437b-aad4-2f9611df11b9 · outbound

This paper cites Scaffold-based molecular design using graph generative model.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Scaffold-based molecular design using graph generative model

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:26:50.546126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 38b87644-be85-4e37-b39a-a2255cba1498 · outbound

This paper cites J.; Bento, A.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning J.; Bento, A

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.822796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36a6a34b-3ff1-4ed7-b872-e39280f9db7e · outbound

This paper cites R.; Paolini, G.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning R.; Paolini, G

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.808450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa89c916-54c7-4ede-bbb3-96dec2bfe7ed · outbound

This paper cites Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.790664Z

Source-reported events for the cited work

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Observation 474e0190-eb09-4a85-8fd1-55c3a9d8acd6 · outbound

This paper cites P.; Welling, M.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning P.; Welling, M

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.774968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 270db600-2c49-4f0f-b599-36378a66c901 · outbound

This paper cites R.; Vilnis, L.; Vinyals, O.; Dai, A.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning R.; Vilnis, L.; Vinyals, O.; Dai, A

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.760450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 650e289a-e4ff-4d92-865c-e486bf156bb0 · outbound

This paper cites beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.745375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d4c46460-27a7-4400-9762-c9a76fb18d68 · outbound

This paper cites ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:26:50.524190Z

Source-reported events for the cited work

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Observation bd87c022-7140-4ee5-8127-e8fb827d516f · outbound

This paper cites Mmd gan: Towards deeper understanding of moment matching network.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Mmd gan: Towards deeper understanding of moment matching network

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.730824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28e78e2f-3882-4145-839f-1e0183a6d855 · outbound

This paper cites H.; Taylor, G.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning H.; Taylor, G

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.716243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 376ff329-e8e1-41da-af89-87526122698a · outbound

This paper cites Wasserstein GAN.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Wasserstein GAN

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.700049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 70e25938-7718-40a3-95c7-736a9dcde382 · outbound

This paper cites Frechet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Frechet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.685153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation beb75164-cb08-44cb-8ce2-dec4244a98cd · outbound

This paper cites an unresolved cited work.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:26:50.668531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a264ab76-cad8-4c7d-8130-2512b535fc36 · outbound

This paper cites an unresolved cited work.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:26:50.651498Z

Source-reported events for the cited work

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Observation 3e6122a6-7380-44e6-9b99-9c64f95fa711 · outbound

This paper cites P.; Salimans, T.; Duan, Y.; Dhariwal, P.; Schulman, J.; Sutskever, I.; Abbeel, P.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning P.; Salimans, T.; Duan, Y.; Dhariwal, P.; Schulman, J.; Sutskever, I.; Abbeel, P

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:26:50.634785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 08ec85fd-18bd-41d6-9531-45df1d28a9e0 · outbound

This paper cites 6DTpDQ 2(C.

DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning 6DTpDQ 2(C

Reference 41

Resolution: malformed identifier; no resolver link, observed 2026-08-14T12:26:50.347920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.