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Paper Citation Record · LEDGER

AlphaFold Database Debiasing for Robust Inverse Folding

As of 11 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 0 inbound Pith citation observations for arXiv:2506.08365.

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

pith.paper-citation-record.v1
2506.08365 v1

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:19:22.806644Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

89 of 89 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8d75aeb-a09b-4906-a16f-b8c8d1dd5048 · outbound

This paper cites Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021.

AlphaFold Database Debiasing for Robust Inverse Folding Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021

Reference 1

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Observation 5d30f47e-6dd8-40dd-8d8f-37bb72b2eb35 · outbound

This paper cites Protein complex prediction with alphafold-multimer.biorxiv, pages 2021–10, 2021.

AlphaFold Database Debiasing for Robust Inverse Folding Protein complex prediction with alphafold-multimer.biorxiv, pages 2021–10, 2021

Reference 2

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Observation dc4348a7-c4d9-44da-9d71-89f2f9171186 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, 630(8016):493–500, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, 630(8016):493–500, 2024

Reference 3

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Observation f9d503b3-6e8c-4337-9eac-0ff56632da8a · outbound

This paper cites Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.Nucleic acids research, 50(D1):D439–D444, 2022.

AlphaFold Database Debiasing for Robust Inverse Folding Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.Nucleic acids research, 50(D1):D439–D444, 2022

Reference 4

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Observation ee4d7f93-8661-4dd5-9c14-e579ff60aaeb · outbound

This paper cites Alphafold protein structure database in 2024: providing structure coverage for over 214 million protein sequences.Nucleic acids research, 52(D1):D368–D375, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Alphafold protein structure database in 2024: providing structure coverage for over 214 million protein sequences.Nucleic acids research, 52(D1):D368–D375, 2024

Reference 5

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Observation 1c6ccf15-ee31-4aa1-848a-341098035cc5 · outbound

This paper cites The case for post-predictional modifications in the alphafold protein structure database.Nature structural & molecular biology, 28(11):869–870, 2021.

AlphaFold Database Debiasing for Robust Inverse Folding The case for post-predictional modifications in the alphafold protein structure database.Nature structural & molecular biology, 28(11):869–870, 2021

Reference 6

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Observation 47872b74-ae4b-488e-92cb-1fd1bbca96e4 · outbound

This paper cites Generative models for graph-based protein design.Advances in neural information processing systems, 32, 2019.

AlphaFold Database Debiasing for Robust Inverse Folding Generative models for graph-based protein design.Advances in neural information processing systems, 32, 2019

Reference 7

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Observation 3a7bb0c5-7981-425c-a2c0-8bc08c49bcc2 · outbound

This paper cites Learning from protein structure with geometric vector perceptrons.

AlphaFold Database Debiasing for Robust Inverse Folding Learning from protein structure with geometric vector perceptrons

Reference 8

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Observation a30e93ed-1f6b-483c-b52b-918cf701e393 · outbound

This paper cites Pifold: Toward effective and efficient protein inverse folding.

AlphaFold Database Debiasing for Robust Inverse Folding Pifold: Toward effective and efficient protein inverse folding

Reference 9

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Observation b4ccfe08-fb05-426a-8f9e-00310de183dc · outbound

This paper cites Chai-1: Decoding the molecular interactions of life.bioRxiv, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Chai-1: Decoding the molecular interactions of life.bioRxiv, 2024

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 19921431-0123-4a6f-88c6-7fb58afee472 · outbound

This paper cites Boltz-1: Democratizing biomolecular interaction modeling.bioRxiv, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Boltz-1: Democratizing biomolecular interaction modeling.bioRxiv, 2024

Reference 11

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Observation 10b8874c-6013-472e-b30f-68b6dc2ed539 · outbound

This paper cites Colabfold: making protein folding accessible to all.Nature methods, 2022.

AlphaFold Database Debiasing for Robust Inverse Folding Colabfold: making protein folding accessible to all.Nature methods, 2022

Reference 12

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 34884b4e-64f5-4be4-a168-70f51dd926a7 · outbound

This paper cites The protein data bank.Nucleic acids research, 28(1):235–242, 2000.

AlphaFold Database Debiasing for Robust Inverse Folding The protein data bank.Nucleic acids research, 28(1):235–242, 2000

Reference 13

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Observation 0ef8315a-4bb8-4d66-9311-ef4a256d41c6 · outbound

This paper cites Highly accurate protein structure prediction for the human proteome.Nature, 596(7873):590–596, 2021.

AlphaFold Database Debiasing for Robust Inverse Folding Highly accurate protein structure prediction for the human proteome.Nature, 596(7873):590–596, 2021

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8dcff36d-2314-40ac-a749-f32d9df683e8 · outbound

This paper cites Saprot: Protein language modeling with structure-aware vocabulary.

AlphaFold Database Debiasing for Robust Inverse Folding Saprot: Protein language modeling with structure-aware vocabulary

Reference 15

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Observation 771e6c9c-c944-4c7d-9d82-34d55a3b68d6 · outbound

This paper cites Protrek: Navigating the protein universe through tri-modal contrastive learning.bioRxiv, pages 2024–05, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Protrek: Navigating the protein universe through tri-modal contrastive learning.bioRxiv, pages 2024–05, 2024

Reference 16

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Observation a37767f6-dd33-42ee-8c18-ba708d810db7 · outbound

This paper cites Improved prediction of protein-protein interactions using alphafold2.Nature communications, 13(1):1265, 2022.

AlphaFold Database Debiasing for Robust Inverse Folding Improved prediction of protein-protein interactions using alphafold2.Nature communications, 13(1):1265, 2022

Reference 17

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 51bb02ab-fe8d-48c8-962d-cb6c5eecbf64 · outbound

This paper cites Cross-gate mlp with protein complex invariant embedding is a one-shot antibody designer.

AlphaFold Database Debiasing for Robust Inverse Folding Cross-gate mlp with protein complex invariant embedding is a one-shot antibody designer

Reference 18

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Observation 34a669a7-6ba4-46f0-bcd3-32802cefb6f0 · outbound

This paper cites dyab: Flow matching for flexible antibody design with alphafold-driven pre-binding antigen.

AlphaFold Database Debiasing for Robust Inverse Folding dyab: Flow matching for flexible antibody design with alphafold-driven pre-binding antigen

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation a318c0bc-d2b3-47c9-a5d3-fdb17b53b6d9 · outbound

This paper cites Foldtoken: Learning protein language via vector quantization and beyond.

AlphaFold Database Debiasing for Robust Inverse Folding Foldtoken: Learning protein language via vector quantization and beyond

Reference 20

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Observation a7fcf449-e7fb-4193-9a40-a1806cc709a4 · outbound

This paper cites Alphafold meets flow matching for generating protein ensembles.

AlphaFold Database Debiasing for Robust Inverse Folding Alphafold meets flow matching for generating protein ensembles

Reference 21

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Observation 4f41b485-b34d-4eac-b4fb-c8f974e204c5 · outbound

This paper cites Machine learning for functional protein design.Nature biotechnology, 42(2):216–228, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Machine learning for functional protein design.Nature biotechnology, 42(2):216–228, 2024

Reference 22

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Observation 3686b312-4019-4535-a401-0fa0f4b14d39 · outbound

This paper cites Sparks of function by de novo protein design.

AlphaFold Database Debiasing for Robust Inverse Folding Sparks of function by de novo protein design

Reference 23

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Observation 0a17929b-77b2-4887-86d7-7f7be926a472 · outbound

This paper cites A text-guided protein design framework.

AlphaFold Database Debiasing for Robust Inverse Folding A text-guided protein design framework

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 456b82a2-3ae7-49c8-99fa-ceb07358f27e · outbound

This paper cites Ribodiffusion: ter- tiary structure-based rna inverse folding with generative diffusion models.Bioinformatics, 40(Supplement_1):i347–i356, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Ribodiffusion: ter- tiary structure-based rna inverse folding with generative diffusion models.Bioinformatics, 40(Supplement_1):i347–i356, 2024

Reference 25

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verified fuzzy
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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 122188b1-c878-4302-8977-d17ed2749a4c · outbound

This paper cites Native protein sequences are close to optimal for their structures.Proceedings of the National Academy of Sciences, 97(19):10383–10388, 2000.

AlphaFold Database Debiasing for Robust Inverse Folding Native protein sequences are close to optimal for their structures.Proceedings of the National Academy of Sciences, 97(19):10383–10388, 2000

Reference 26

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Source-reported events for the cited work

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Observation 072c45a5-b889-42fb-9a37-af9fac77d8b5 · outbound

This paper cites De novo protein design by deep network hallucination.Nature, 600(7889):547–552, 2021.

AlphaFold Database Debiasing for Robust Inverse Folding De novo protein design by deep network hallucination.Nature, 600(7889):547–552, 2021

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 4fa20b8d-b056-4889-b358-999f0d5e0bbb · outbound

This paper cites Protein sequence design with a learned potential.Nature communi- cations, 13(1):746, 2022.

AlphaFold Database Debiasing for Robust Inverse Folding Protein sequence design with a learned potential.Nature communi- cations, 13(1):746, 2022

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 52a43eef-6b59-4b4b-a23f-a480e65e9403 · outbound

This paper cites Proteina: Scaling flow-based protein structure generative models.

AlphaFold Database Debiasing for Robust Inverse Folding Proteina: Scaling flow-based protein structure generative models

Reference 29

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.594744Z digest=sha256:a7f43554a6f07a55458adb3d78fae1896101e6ebc706d2e49bbde73634e5f670

Observation d1aab0e8-9aea-4fbd-aba2-fb94a55c2e75 · outbound

This paper cites Protcomposer: Compositional protein structure generation with 3d ellipsoids.

AlphaFold Database Debiasing for Robust Inverse Folding Protcomposer: Compositional protein structure generation with 3d ellipsoids

Reference 30

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raw_fallback, observed 2026-08-07T05:19:23.402240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.598659Z digest=sha256:576396b100a9b336cadf5758b7747b375e2affdf0482ad94a49f90ff7cd5c568

Observation 07372d91-9c82-4521-b8e2-a25f5fa1fb7b · outbound

This paper cites De novo protein design: fully automated sequence selection.Science, 278(5335):82–87, 1997.

AlphaFold Database Debiasing for Robust Inverse Folding De novo protein design: fully automated sequence selection.Science, 278(5335):82–87, 1997

Reference 31

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raw_fallback, observed 2026-08-07T05:19:23.393274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.602201Z digest=sha256:b191fd8b281cc0e6e003f774f1c9a3c115c6fbfbac4409a23d19328f8699ca56

Observation 3704b734-5361-40ca-aecb-d7962adf8f5f · outbound

This paper cites Spherical convolutions and their application in molecular modelling.Advances in neural information processing systems, 30, 2017.

AlphaFold Database Debiasing for Robust Inverse Folding Spherical convolutions and their application in molecular modelling.Advances in neural information processing systems, 30, 2017

Reference 32

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raw_fallback, observed 2026-08-07T05:19:23.383824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.605882Z digest=sha256:bd1afc2284247e1382fd637dbdd75e68f2990edf832db0869f2458e53227f521

Observation 3b5024b4-9a6b-49ed-9bb4-ced307dd4e6d · outbound

This paper cites A survey on generative diffusion models.IEEE Transactions on Knowledge and Data Engineering, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding A survey on generative diffusion models.IEEE Transactions on Knowledge and Data Engineering, 2024

Reference 33

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raw_fallback, observed 2026-08-07T05:19:23.374023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.609733Z digest=sha256:e2d7670627d25f67606a2dcfdf2aae0dceea455774fc610c8cbe8528abd86e0a

Observation 33d6aeec-03a8-4163-836a-b5a4bc214c9b · outbound

This paper cites Fold2seq: A joint sequence (1d)-fold (3d) embedding-based generative model for protein design.

AlphaFold Database Debiasing for Robust Inverse Folding Fold2seq: A joint sequence (1d)-fold (3d) embedding-based generative model for protein design

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.363293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.613610Z digest=sha256:fa168fc153c2c11774367e3a04bfccb88f918c2fffef972bac5ad21c65e4f219

Observation 43c52279-02ea-4d68-8685-abff16262519 · outbound

This paper cites an unresolved cited work.

AlphaFold Database Debiasing for Robust Inverse Folding Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:19:23.352879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.617823Z digest=sha256:db405643d223dd8ca136067807c67ab25a7e84c46114681d7fc93e515f27b64e

Observation f77f889d-8d23-4076-9065-4a0358ee4a0a · outbound

This paper cites Spin2: Predicting sequence profiles from protein structures using deep neural networks.Proteins: Structure, Function, and Bioinformatics, 86(6):629–633, 2018.

AlphaFold Database Debiasing for Robust Inverse Folding Spin2: Predicting sequence profiles from protein structures using deep neural networks.Proteins: Structure, Function, and Bioinformatics, 86(6):629–633, 2018

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.342723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.621692Z digest=sha256:a75a4a7d9867c3890bc86b2a0d7c1b6385d50a6944e8dfe85740e61a84ea8caa

Observation 835e5b02-6e88-4d64-b058-8ef6ef1369d2 · outbound

This paper cites Computational protein design with deep learning neural networks.Scientific reports, 8(1):1–9, 2018.

AlphaFold Database Debiasing for Robust Inverse Folding Computational protein design with deep learning neural networks.Scientific reports, 8(1):1–9, 2018

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.332787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.625768Z digest=sha256:6a2c9f6e764d6486790f720f40c6eab66b5ceb29175dd09f564f7ee5379a9965

Observation 4f5df1e8-a349-4304-b576-4500ad7ff5f8 · outbound

This paper cites To improve protein sequence profile prediction through image captioning on pairwise residue distance map.Journal of chemical information and modeling, 60(1):391–399, 2019.

AlphaFold Database Debiasing for Robust Inverse Folding To improve protein sequence profile prediction through image captioning on pairwise residue distance map.Journal of chemical information and modeling, 60(1):391–399, 2019

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.322688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.629015Z digest=sha256:35b8e39f43d4477d9dd07a5b7c25436ef9ca02be632c5aeebf89e14ce3e19a59

Observation 3b140a28-f9b0-4c0a-a47b-3102e54156bb · outbound

This paper cites Densecpd: improving the accuracy of neural-network-based computational protein sequence design with densenet.Journal of chemical information and modeling, 60(3):1245–1252, 2020.

AlphaFold Database Debiasing for Robust Inverse Folding Densecpd: improving the accuracy of neural-network-based computational protein sequence design with densenet.Journal of chemical information and modeling, 60(3):1245–1252, 2020

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.313248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.632655Z digest=sha256:7b95f31cb5eccd424bb8b08d6a36e1363b8a35fce749b14e1b7457ec364065fe

Observation 579a0873-55ee-4f10-a872-45b5a7874344 · outbound

This paper cites Prodconn: Protein design using a convolutional neural network.Proteins: Structure, Function, and Bioinformatics, 88(7):819–829, 2020.

AlphaFold Database Debiasing for Robust Inverse Folding Prodconn: Protein design using a convolutional neural network.Proteins: Structure, Function, and Bioinformatics, 88(7):819–829, 2020

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.303923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.636220Z digest=sha256:d88a5315766736567a2017231dd7a59f7ae90b67aff505020414b7ff386b44e9

Observation d3a27b66-c9b0-4895-8fb7-d0b26f3b0546 · outbound

This paper cites Densely connected convolutional networks.

AlphaFold Database Debiasing for Robust Inverse Folding Densely connected convolutional networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.640087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.640087Z digest=sha256:99db5fc43b2fdb4a51dc62ed60a1284897a89f03d2d50df1f3a0496298a31bbd

Observation 6c7c5744-97f2-4337-bad0-06b47f738d99 · outbound

This paper cites Graph denoising diffusion for inverse protein folding.Advances in Neural Information Processing Systems, 36:10238– 10257, 2023.

AlphaFold Database Debiasing for Robust Inverse Folding Graph denoising diffusion for inverse protein folding.Advances in Neural Information Processing Systems, 36:10238– 10257, 2023

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.287587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.643863Z digest=sha256:a12565fff28cc6914e9598aa898bf452631c1e3e3c567d965bf1673d1d177d92

Observation 909fea82-5bfd-42d4-a80e-ffa5c76a77b2 · outbound

This paper cites Bridge-if: Learning inverse protein folding with markov bridges.

AlphaFold Database Debiasing for Robust Inverse Folding Bridge-if: Learning inverse protein folding with markov bridges

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.277423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.647388Z digest=sha256:5c9c1e2859e2cab1172bad4bc6d393a539d1a8510549908104c6974f89aa0500

Observation cf9b07de-2c04-48e4-b286-ac592c22b276 · outbound

This paper cites A graph is worth k words: Euclideanizing graph using pure transformer.

AlphaFold Database Debiasing for Robust Inverse Folding A graph is worth k words: Euclideanizing graph using pure transformer

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.266616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.650817Z digest=sha256:339a8d81faf5b57f9b627278b3db8f8495b6b7b7e794cb5cf79bfc91468c3754

Observation 4479ef32-43a8-4058-be9f-07bc86f7e366 · outbound

This paper cites Global-context aware generative protein design.

AlphaFold Database Debiasing for Robust Inverse Folding Global-context aware generative protein design

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.255450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.654092Z digest=sha256:59cb3c6a57daf0fd1ef1237afcb899b55c45284a1a322abfa50244dc4c8c71e2

Observation b6d44b40-619a-4d8d-a246-71f0cea24cb6 · outbound

This paper cites Fast and flexible protein design using deep graph neural networks.Cell Systems, 11(4):402–411, 2020.

AlphaFold Database Debiasing for Robust Inverse Folding Fast and flexible protein design using deep graph neural networks.Cell Systems, 11(4):402–411, 2020

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.244946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.657187Z digest=sha256:ca806b7c2e9dc9beb0abc2bc6c5fda1f4d1db25fc21c489b40279417f6b57dc6

Observation d90ac799-41ce-44a0-b1f7-10492d425cfe · outbound

This paper cites AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB.

AlphaFold Database Debiasing for Robust Inverse Folding AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.660459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.660459Z digest=sha256:3383f13d1e482ca3efd5d0db40b4ff61b82e3beab9a2d8690a3be036b5a72262

Observation bc10b24a-8841-476f-a82c-f94b8227924b · outbound

This paper cites Robust deep learning–based protein sequence design using proteinmpnn.Science, 378(6615):49–56, 2022.

AlphaFold Database Debiasing for Robust Inverse Folding Robust deep learning–based protein sequence design using proteinmpnn.Science, 378(6615):49–56, 2022

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.664370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.664370Z digest=sha256:bcf14e668ff00a92bb7e3792ce2944199673705ea20ed3decad58c3c7e65b5b5

Observation 40c7dd4d-fb56-4a92-9fa8-822006a52bb2 · outbound

This paper cites Learning inverse folding from millions of predicted structures.

AlphaFold Database Debiasing for Robust Inverse Folding Learning inverse folding from millions of predicted structures

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.668266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.668266Z digest=sha256:47ca275977f39e7e1d210de3a49d25dd6a666445bbca0e4b12d501ad214a0059

Observation b3d488cb-f8df-4561-94ce-e3416fe44f88 · outbound

This paper cites De novo protein design using geometric vector field networks.

AlphaFold Database Debiasing for Robust Inverse Folding De novo protein design using geometric vector field networks

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.223941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.671929Z digest=sha256:2ee432c5b128477054973bb33c2d052cf3491842302363252c071a732f8a33bb

Observation bf25091a-225b-4673-9411-68871d0f2dc3 · outbound

This paper cites Boltzmann-aligned inverse folding model as a predictor of mutational effects on protein-protein interactions.

AlphaFold Database Debiasing for Robust Inverse Folding Boltzmann-aligned inverse folding model as a predictor of mutational effects on protein-protein interactions

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.213001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.675063Z digest=sha256:3fc5dd5efc1c0c2b7384d7181874a06fa8877f957a9a5dd4c58cea37f4907d92

Observation 89982693-ad46-47a7-997a-dcb059b6c258 · outbound

This paper cites Structure- informed language models are protein designers.

AlphaFold Database Debiasing for Robust Inverse Folding Structure- informed language models are protein designers

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.678325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.678325Z digest=sha256:fed7d73204474629f6f6831b2b5568618ac37b9826ecd12cc9c966555e061c0a

Observation fdc5d8c9-7d8c-4c7d-9ea2-58b6e4a8dfc1 · outbound

This paper cites Kw-design: Pushing the limit of protein design via knowledge refinement.

AlphaFold Database Debiasing for Robust Inverse Folding Kw-design: Pushing the limit of protein design via knowledge refinement

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.195996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.681493Z digest=sha256:ffb5a2a5a5b175becd06dab0f94626600b92710a000e68504562a2afae4770dd

Observation a160f1cc-d081-4050-b53d-fc1e3eac9843 · outbound

This paper cites Diffusion language models are versatile protein learners.

AlphaFold Database Debiasing for Robust Inverse Folding Diffusion language models are versatile protein learners

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.186726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.685603Z digest=sha256:90e3e808993e0748b258c25793a86483bac399d5eb7a1926e577dc292526b9d9

Observation ff06e750-427a-4e9a-9ca9-095c1836c892 · outbound

This paper cites Dplm-2: A multimodal diffusion protein language model.

AlphaFold Database Debiasing for Robust Inverse Folding Dplm-2: A multimodal diffusion protein language model

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.177747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.688654Z digest=sha256:80550f63f944ea69b655313c89a2b1444bf0ef0204c678671793972aeb2029b6

Observation 6442e8eb-939e-4cd3-9e9b-84f3411edfd7 · outbound

This paper cites Surfpro: Functional protein design based on continuous surface.

AlphaFold Database Debiasing for Robust Inverse Folding Surfpro: Functional protein design based on continuous surface

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.168514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.691570Z digest=sha256:943c1e58ffd5c7cbec3cde16d824e61a9fb01abd1c452c105137c35dd2c63c92

Observation cd74648a-f798-4fd4-bcdf-34e566c04217 · outbound

This paper cites Bc-design: A biochemistry-aware framework for highly accurate inverse protein folding.bioRxiv, pages 2024–10, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Bc-design: A biochemistry-aware framework for highly accurate inverse protein folding.bioRxiv, pages 2024–10, 2024

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.159055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.695259Z digest=sha256:df0c7353754cc50b6c403112f6024e7a8c6eed0988a6f59bc445c3d286532183

Observation 548080d7-bc79-4cd8-9bbe-494d4aa44888 · outbound

This paper cites Equibind: Geometric deep learning for drug binding structure prediction.

AlphaFold Database Debiasing for Robust Inverse Folding Equibind: Geometric deep learning for drug binding structure prediction

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.149363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.698571Z digest=sha256:7d63758ed1d4ad79e538ac8c0437f6accea021d8e5b0a906aff81ade71bc7999

Observation ff93ce52-008b-4442-be9f-2cbac44edd9b · outbound

This paper cites Diff- dock: Diffusion steps, twists, and turns for molecular docking.

AlphaFold Database Debiasing for Robust Inverse Folding Diff- dock: Diffusion steps, twists, and turns for molecular docking

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.138626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.701901Z digest=sha256:88bd595514ee0c60718f8859dec41da86c4efb6c585cd680c560ea4084c72cfc

Observation 396557e6-af80-4c54-90de-7355e35f320f · outbound

This paper cites an unresolved cited work.

AlphaFold Database Debiasing for Robust Inverse Folding Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:19:23.127169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.705880Z digest=sha256:cb265f42050c535274088c3ab1516b4494e79e34c6b3c1f870fdfdbfb625b534

Observation df1d3f4a-f96a-426b-a3fe-e19f0e4ad0d1 · outbound

This paper cites Conditional antibody design as 3d equivariant graph translation.

AlphaFold Database Debiasing for Robust Inverse Folding Conditional antibody design as 3d equivariant graph translation

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.116040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.709326Z digest=sha256:8010afd4ba5a79d35b782d6717818507be96805c1e0db97af7c1b82038cbcdc5

Observation 62dac6bb-2dd2-4bcc-957a-df4ce2c28cef · outbound

This paper cites End-to-end full-atom antibody design.

AlphaFold Database Debiasing for Robust Inverse Folding End-to-end full-atom antibody design

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.106327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.713369Z digest=sha256:7ca529e2e04f927c1e9a707a3e479cb847d6e9ab008d5116ad65ac8c9333d5b7

Observation 0fe4a810-6b4a-4bba-88c5-e98f10fd0912 · outbound

This paper cites Deep- pocket: ligand binding site detection and segmentation using 3d convolutional neural networks.

AlphaFold Database Debiasing for Robust Inverse Folding Deep- pocket: ligand binding site detection and segmentation using 3d convolutional neural networks

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.097444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.716605Z digest=sha256:f04ef0a36c445b88bb00037f1fe70622ff5c1da771cec77a6d827b5cf679d48e

Observation 48599698-3748-43b4-84cb-0adf36ae0728 · outbound

This paper cites Pre-training with fractional denoising to enhance molecular property prediction.

AlphaFold Database Debiasing for Robust Inverse Folding Pre-training with fractional denoising to enhance molecular property prediction

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.088051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.719489Z digest=sha256:ae0025c4f8c92abf777e01c0e32fdf9d62440de3bc7ddc2ede93f3d5aea8d960

Observation ca34d095-b8df-49de-ab72-59b84f260a3b · outbound

This paper cites Spherical message passing for 3d molecular graphs.

AlphaFold Database Debiasing for Robust Inverse Folding Spherical message passing for 3d molecular graphs

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.077712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.722735Z digest=sha256:43cefce56c7960350c7d478436fc9b59ea111f45f609520a0a4c6e8a733ebdc0

Observation 173b53b3-e670-4f9a-b4af-aa60d31a83ee · outbound

This paper cites Protst: Multi-modality learning of protein sequences and biomedical texts.

AlphaFold Database Debiasing for Robust Inverse Folding Protst: Multi-modality learning of protein sequences and biomedical texts

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.726139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.726139Z digest=sha256:e4cf6c4679f15abc1a6a8ba2226c541ccc033431722049ff972b91ab81e8c009

Observation fbd138ea-e704-4f4e-94ab-73570eabc78d · outbound

This paper cites Deepre: sequence-based enzyme ec number prediction by deep learning.Bioinformatics, 34(5):760–769, 2018.

AlphaFold Database Debiasing for Robust Inverse Folding Deepre: sequence-based enzyme ec number prediction by deep learning.Bioinformatics, 34(5):760–769, 2018

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.062841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.729574Z digest=sha256:e3da7062272e24a2bc3418286a4146a57676498376cea2cea06713dcffe58d38

Observation 26b78ee5-ec0f-4306-a280-14e4404271ba · outbound

This paper cites Proteingym: Large- scale benchmarks for protein fitness prediction and design.Advances in Neural Information Processing Systems, 36:64331–64379, 2023.

AlphaFold Database Debiasing for Robust Inverse Folding Proteingym: Large- scale benchmarks for protein fitness prediction and design.Advances in Neural Information Processing Systems, 36:64331–64379, 2023

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.051579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.733565Z digest=sha256:58a31b21b7b9199839a0567ad5c3854e209611f73fc75ecc0a6ad5970c64dfcf

Observation bf0d5c49-1ce9-46fe-a527-9d62f34c7a2d · outbound

This paper cites Reactzyme: A benchmark for enzyme-reaction prediction.Advances in Neural Information Processing Systems, 37:26415–26442, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Reactzyme: A benchmark for enzyme-reaction prediction.Advances in Neural Information Processing Systems, 37:26415–26442, 2024

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.042392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.737399Z digest=sha256:e1ffa5c463dc50cc118c2445a917b49671334b691a78df9ef05bb1e70cee4a9d

Observation 8c912596-4ef9-4bb4-9f3a-0fa2c4fa3963 · outbound

This paper cites Continuous-discrete convolu- tion for geometry-sequence modeling in proteins.

AlphaFold Database Debiasing for Robust Inverse Folding Continuous-discrete convolu- tion for geometry-sequence modeling in proteins

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.032141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.740951Z digest=sha256:9b68c39460f649e025aecbad3b4c1a4c6ec64dbe4dddaf9d403740cdb9176f94

Observation 54f478de-10b5-47d1-bc2b-faf023cc165a · outbound

This paper cites Symmetry-informed geometric representation for molecules, proteins, and crystalline materials.Advances in neural information processing systems, 36:66084–66101, 2023.

AlphaFold Database Debiasing for Robust Inverse Folding Symmetry-informed geometric representation for molecules, proteins, and crystalline materials.Advances in neural information processing systems, 36:66084–66101, 2023

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.022967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.744753Z digest=sha256:99f8792459247451971c1e749fc36f522ebdc407f0eaa26ce611588c448c751b

Observation a99be384-3608-4619-91d6-92f4a74eda0e · outbound

This paper cites Learning hierarchical protein representations via complete 3d graph networks.

AlphaFold Database Debiasing for Robust Inverse Folding Learning hierarchical protein representations via complete 3d graph networks

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:23.012531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.748214Z digest=sha256:53b5c0b59070b47d4cef60f879ceded0e1b86edd8487a563e0ebfcda404bcfd3

Observation 78c4d362-ee84-4bfd-9438-80b3178b89cb · outbound

This paper cites De novo design of protein interactions with learned surface fingerprints.Nature, 617(7959):176–184, 2023.

AlphaFold Database Debiasing for Robust Inverse Folding De novo design of protein interactions with learned surface fingerprints.Nature, 617(7959):176–184, 2023

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.751299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.751299Z digest=sha256:66173f401eb8235e9fdbfc21dd22880b7d4aeaca7c0855732d28f33ab38624a1

Observation 90ac2bd6-83e2-4fe3-8a02-c134aef2943c · outbound

This paper cites Kermut: Composite kernel regression for protein variant effects.Advances in Neural Information Processing Systems, 37:29514–29565, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Kermut: Composite kernel regression for protein variant effects.Advances in Neural Information Processing Systems, 37:29514–29565, 2024

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.997232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.754317Z digest=sha256:2d94d1ab0a493ea06e28582a84ea744aa8cd6df71b9a2a1c43e984a49acfdab4

Observation 48bdf3b7-6690-47b5-9185-90e02b33ec13 · outbound

This paper cites Relation-aware equivariant graph networks for epitope-unknown antibody design and specificity optimization.

AlphaFold Database Debiasing for Robust Inverse Folding Relation-aware equivariant graph networks for epitope-unknown antibody design and specificity optimization

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.987355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.757404Z digest=sha256:36b885a572f36f4af6eeb8150d8ebac142aa3771b14b625a4c790933be18a528

Observation 806c9698-d4e6-444d-b023-3e40cc932b6b · outbound

This paper cites Metoken: Uniform micro-environment token boosts post- translational modification prediction.

AlphaFold Database Debiasing for Robust Inverse Folding Metoken: Uniform micro-environment token boosts post- translational modification prediction

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.976451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.761182Z digest=sha256:7a00f7abb9b09fae256aae935615dcfbe4e5425713c6693a8ec0a6df903d7f8a

Observation 824074a2-2843-404d-96f4-94673ef56a96 · outbound

This paper cites SAGEPhos: Sage bio-coupled and augmented fusion for phosphorylation site detection.

AlphaFold Database Debiasing for Robust Inverse Folding SAGEPhos: Sage bio-coupled and augmented fusion for phosphorylation site detection

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.966320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.764226Z digest=sha256:a952ee3e41ba1816e169dae72cbb02fc0cf64b7904376257ced273ef88fca7ec

Observation e56b66b6-d767-468e-bcaa-a5254244bcf3 · outbound

This paper cites Cath–a hierarchic classification of protein domain structures.Structure, 5(8):1093–1109, 1997.

AlphaFold Database Debiasing for Robust Inverse Folding Cath–a hierarchic classification of protein domain structures.Structure, 5(8):1093–1109, 1997

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.955096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.767375Z digest=sha256:4a3d3524c23cb2ae3dc02422051feef04f1fdf0a9d34adf7466475d8cb2847f4

Observation d4b53acb-a455-4673-a16b-a9f34cf1369a · outbound

This paper cites Illumi- nating protein space with a programmable generative model.Nature, 623(7989):1070–1078, 2023.

AlphaFold Database Debiasing for Robust Inverse Folding Illumi- nating protein space with a programmable generative model.Nature, 623(7989):1070–1078, 2023

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.943997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.770947Z digest=sha256:72a124516043e7ff0c8c96695753cd69e511c053925e06a205279ff035ab7754

Observation bd5fc426-755f-492d-a3ec-1764269a5ef2 · outbound

This paper cites Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature biotechnology, 35(11):1026–1028, 2017.

AlphaFold Database Debiasing for Robust Inverse Folding Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature biotechnology, 35(11):1026–1028, 2017

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:22.774381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:22.774381Z digest=sha256:3df255598ed4cf3182737e37f6d18fc74844d8d2f1c6f0e0c03cb5d24195ac79

Observation 25f5052c-104a-4ff5-b372-27e700bb9d0e · outbound

This paper cites Gpu- accelerated homology search with mmseqs2.bioRxiv, pages 2024–11, 2024.

AlphaFold Database Debiasing for Robust Inverse Folding Gpu- accelerated homology search with mmseqs2.bioRxiv, pages 2024–11, 2024

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.928967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.777375Z digest=sha256:125ed0ae9796ad98f6903529eb51f9ff55c6620aa6d24bd33d692e4e2119aa15

Observation f9ca2507-af84-4568-ba3e-29926ee781ec · outbound

This paper cites an unresolved cited work.

AlphaFold Database Debiasing for Robust Inverse Folding Unresolved cited work

Reference 82

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:19:22.920160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.781398Z digest=sha256:3d4758c90c3c62c8cd2aa9de9e9bbe94c9d089733644406fcd5da985d94dcc35

Observation c3d65af2-5c54-4244-8c78-2a5a488c82da · outbound

This paper cites The curation process for this paired dataset involved several steps:.

AlphaFold Database Debiasing for Robust Inverse Folding The curation process for this paired dataset involved several steps:

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.909935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.784925Z digest=sha256:23bc980f6af29b21327dcb71aa554e7117b15b4f14369f61363d1e7652ff715c

Observation 7eb0b98c-fefb-4220-ac9a-9becd9dcb547 · outbound

This paper cites an unresolved cited work.

AlphaFold Database Debiasing for Robust Inverse Folding Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:19:22.900082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.788617Z digest=sha256:6cc6700e940a27e6867cd881a9166e183f22c8515a7441a666a5bd7e12a6f60b

Observation 490cf0fd-ab59-4005-ad04-abc00e3335ee · outbound

This paper cites • The sequence lengths of the AFDB-predicted structure and the PDB experimental structure must be identical.

AlphaFold Database Debiasing for Robust Inverse Folding • The sequence lengths of the AFDB-predicted structure and the PDB experimental structure must be identical

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.888415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.792259Z digest=sha256:0246db7a0c4693b82e25a701b6a6482f78388bd38f5a6587374ee3500af8a922

Observation ffece9bc-4d0e-4cf7-8e90-2a0e82292cdf · outbound

This paper cites This curation process yielded a high-quality dataset of19,392 AFDB-PDB paired structures.

AlphaFold Database Debiasing for Robust Inverse Folding This curation process yielded a high-quality dataset of19,392 AFDB-PDB paired structures

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:22.878865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.795879Z digest=sha256:cec35fe8ff3cab484bc0db0147d33b4fb31215aeedd62e8ba36d3d93b461893b

Observation e9515810-6f77-4aef-ac32-95404da16a95 · outbound

This paper cites an unresolved cited work.

AlphaFold Database Debiasing for Robust Inverse Folding Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:19:22.868447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.799815Z digest=sha256:a28a289ef7cfd2768ae4d8e8d699ffd15a71c418e78203c5848109929f7fc828

Observation 164852ac-42d3-4c46-ba1a-7334d8866a0e · outbound

This paper cites an unresolved cited work.

AlphaFold Database Debiasing for Robust Inverse Folding Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:19:22.859281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.802952Z digest=sha256:faa53765d049482bcef4fdcb0c3e6f5d156850781f95291e96d29b1d29d47f41

Observation 3dc67ef4-1374-4ac8-92b5-3fffb67851a3 · outbound

This paper cites Debiased AFDB.

AlphaFold Database Debiasing for Robust Inverse Folding Debiased AFDB

Reference 89

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T05:19:22.849412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T05:19:22.806644Z digest=sha256:e33e08e405fc6fb344716b758bf8e78b6e1455569609040d24b3d0fdc8ef9c44

Pith citing papers

No inbound Pith citation observations are available.