VenusX: Unlocking Fine-Grained Functional Understanding of Proteins | Paper Citation Record

Observation d42a0525-f7ee-4237-8bcc-bbeb08ab5264 · outbound

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

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Highly accurate protein structure prediction with AlphaFold.Nature, 596(7873):583–589, 2021

Reference 1

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Observation d7c4754c-2d06-43ae-b041-ed884908e35e · outbound

This paper cites Accurate structure prediction of biomolecular interactions with AlphaFold 3.Nature, pages 1–3, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Accurate structure prediction of biomolecular interactions with AlphaFold 3.Nature, pages 1–3, 2024

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.230228Z

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Observation 79a67369-7b4b-40d7-8227-296897f77826 · outbound

This paper cites Machine learning- aided engineering of hydrolases for PET depolymerization.Nature, 604(7907):662–667, 2022.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Machine learning- aided engineering of hydrolases for PET depolymerization.Nature, 604(7907):662–667, 2022

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.945834Z

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Observation e93f819d-af2d-46d7-a735-6ef8e05daf20 · outbound

This paper cites A conditional protein diffusion model generates artificial programmable endonuclease sequences with enhanced activity.Cell Discovery, 10(1):95, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins A conditional protein diffusion model generates artificial programmable endonuclease sequences with enhanced activity.Cell Discovery, 10(1):95, 2024

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.920793Z

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Observation 07ea00db-fac6-4497-b8b2-2818bef46822 · outbound

This paper cites Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language Model.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language Model

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.247862Z

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Observation 9e4eea15-dbe9-4721-a7cc-f157940818c8 · outbound

This paper cites Enzyme function prediction using contrastive learning.Science, 379(6639):1358–1363, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Enzyme function prediction using contrastive learning.Science, 379(6639):1358–1363, 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.253570Z

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Observation 134d9d99-c28e-45a3-90f0-c13dcbad400a · outbound

This paper cites Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning.Nature Communications, 15(1):5566, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning.Nature Communications, 15(1):5566, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.884866Z

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Observation 06328444-065b-4b59-b2c7-19f299b6a66f · outbound

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

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins CATH – a hierarchic classification of protein domain structures.Structure, 5(8):1093–1109, 1997

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.866969Z

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Observation 4e1c78b3-0058-4308-ad89-550ed48c53a1 · 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.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins 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 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.847581Z

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Observation 0d143272-4cac-4ff3-a9da-713f35414f2e · outbound

This paper cites UniProt: the universal protein knowledgebase in 2025.Nucleic Acids Research, 53(D1):D609–D617, 2025.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins UniProt: the universal protein knowledgebase in 2025.Nucleic Acids Research, 53(D1):D609–D617, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.825797Z

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Observation ec803221-e323-4541-bbbc-f0cac29cd481 · outbound

This paper cites Simple, efficient, and scalable structure-aware adapter boosts protein language models.Journal of Chemical Information and Modeling, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Simple, efficient, and scalable structure-aware adapter boosts protein language models.Journal of Chemical Information and Modeling, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.807568Z

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Observation bbe1b82c-0375-40cb-a11b-21b612466096 · outbound

This paper cites Immunogenicity prediction with dual attention enables vaccine target selection.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Immunogenicity prediction with dual attention enables vaccine target selection

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.790155Z

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Observation 4803cbba-ba25-47ac-8db1-cfda43528f38 · outbound

This paper cites Large-scale prediction of human protein- protein interactions from amino acid sequence based on latent topic features.Journal of Proteome Research, 9(10):4992–5001, 2010.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Large-scale prediction of human protein- protein interactions from amino acid sequence based on latent topic features.Journal of Proteome Research, 9(10):4992–5001, 2010

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.773158Z

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This paper cites an unresolved cited work.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:53:11.755864Z

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Observation dc396b4b-9416-445e-ad3c-9d251a896523 · outbound

This paper cites Skempi 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation.Bioinformatics, 35(3):462–469, 2019.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Skempi 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation.Bioinformatics, 35(3):462–469, 2019

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.310605Z

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Observation ac738482-91fe-4e4b-af35-7e1ea18d7288 · outbound

This paper cites A comprehensive dataset of protein-protein interactions and ligand binding pockets for advancing drug discovery.Scientific Data, 11(1):402, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins A comprehensive dataset of protein-protein interactions and ligand binding pockets for advancing drug discovery.Scientific Data, 11(1):402, 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.720574Z

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Observation e4c043f5-26b9-4f44-9900-1b2d0e06d9f1 · outbound

This paper cites Quan- titative missense variant effect prediction using large-scale mutagenesis data.Cell Systems, 6(1):116–124, 2018.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Quan- titative missense variant effect prediction using large-scale mutagenesis data.Cell Systems, 6(1):116–124, 2018

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.703589Z

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Observation 1c86f260-bda3-4ae3-94fd-eae7e36fa1da · outbound

This paper cites Deep generative models of genetic variation capture the effects of mutations.Nature Methods, 15(10):816–822, 2018.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Deep generative models of genetic variation capture the effects of mutations.Nature Methods, 15(10):816–822, 2018

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.686913Z

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Observation 158348fb-a0b4-488f-b9fe-938349fbdac2 · outbound

This paper cites ProteinGym: large-scale benchmarks for protein fitness prediction and design.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins ProteinGym: large-scale benchmarks for protein fitness prediction and design

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.669633Z

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Observation 44c97d87-99d3-41d8-9416-0157f1e6c50e · outbound

This paper cites Venusmuthub: a systematic evaluation of protein mutation effect predictors on small-scale experimental data.Acta Pharmaceutica Sinica B, 2025.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Venusmuthub: a systematic evaluation of protein mutation effect predictors on small-scale experimental data.Acta Pharmaceutica Sinica B, 2025

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.653255Z

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Observation 71a81df9-1fa8-4246-b218-f30001b4181e · outbound

This paper cites Discovering functionally important sites in proteins.Nature communications, 14(1):4175, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Discovering functionally important sites in proteins.Nature communications, 14(1):4175, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.634745Z

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Observation 435a7edb-d27f-4040-bf9e-0687264c5046 · outbound

This paper cites Predicting protein function from sequence and structure.Nature reviews molecular cell biology, 8(12):995–1005, 2007.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Predicting protein function from sequence and structure.Nature reviews molecular cell biology, 8(12):995–1005, 2007

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.615626Z

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Observation 49e2d6ac-33c7-48fb-b960-3b863b71b97a · outbound

This paper cites Deep- bce: evaluation of deep learning models for identification of immunogenic b-cell epitopes.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Deep- bce: evaluation of deep learning models for identification of immunogenic b-cell epitopes

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.597854Z

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Observation 171b7c4f-f73e-4dda-ada8-84369f85df84 · outbound

This paper cites InterPro in 2022.Nucleic Acids Research, 51(D1):D418–D427, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins InterPro in 2022.Nucleic Acids Research, 51(D1):D418–D427, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.579709Z

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Observation 9b974618-98be-4c3b-a753-32aa003e359a · outbound

This paper cites BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions.Nucleic Acids Research, 41(D1):D1096– D1103, 2012.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions.Nucleic Acids Research, 41(D1):D1096– D1103, 2012

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.562005Z

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Observation b50dd037-356e-4e43-b3d1-08919d2f23bb · outbound

This paper cites SAbDab: the structural antibody database.Nucleic Acids Research, 42(D1):D1140–D1146, 2014.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins SAbDab: the structural antibody database.Nucleic Acids Research, 42(D1):D1140–D1146, 2014

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.542138Z

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Observation ecc5e8da-18a5-4054-aebc-3bfc9a29f06e · outbound

This paper cites an unresolved cited work.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Unresolved cited work

Reference 27

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Observation 22713993-2fb4-4c07-bfaa-2dc106a08437 · outbound

This paper cites Prottrans: Toward understanding the language of life through self-supervised learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10):7112–7127, 2021.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Prottrans: Toward understanding the language of life through self-supervised learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10):7112–7127, 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.507884Z

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Observation f4d175f3-18ab-4915-908b-9c85bc157171 · outbound

This paper cites Ankh: Optimized Protein Language Model Unlocks General-Purpose Modelling.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Ankh: Optimized Protein Language Model Unlocks General-Purpose Modelling

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Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.445692Z

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Observation f3e751bc-2982-4d07-9f07-77c005cdcc34 · outbound

This paper cites ProstT5: Bilingual language model for protein sequence and structure.bioRxiv, pages 2023–07, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins ProstT5: Bilingual language model for protein sequence and structure.bioRxiv, pages 2023–07, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.488394Z

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Observation 1c7d8132-111e-44f3-881f-865ad5db25a9 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.461941Z

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Observation 6c71a887-21ab-4e2a-b217-25f7f677c86f · outbound

This paper cites Protein remote homology detection and structural alignment using deep learning.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Protein remote homology detection and structural alignment using deep learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.447965Z

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Observation 85e0a84e-d608-4bfe-aa0b-e58d046f2f2a · outbound

This paper cites SaProt: protein language modeling with structure-aware vocabulary.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins SaProt: protein language modeling with structure-aware vocabulary

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.426988Z

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Observation e038233d-ef38-4642-be5c-98f43a228cda · outbound

This paper cites Semantical and geo- metrical protein encoding toward enhanced bioactivity and thermostability.eLife, 13:RP98033, may 2025.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Semantical and geo- metrical protein encoding toward enhanced bioactivity and thermostability.eLife, 13:RP98033, may 2025

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.405838Z

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Observation 89f15533-4e03-4df9-9258-5c2e1b79b301 · outbound

This paper cites Masked inverse folding with sequence transfer for protein representation learning.Protein Engineering, Design and Selection, 36:gzad015, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Masked inverse folding with sequence transfer for protein representation learning.Protein Engineering, Design and Selection, 36:gzad015, 2023

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Observation 53cdceb7-f84d-4949-9bd8-5d7e074373c5 · outbound

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

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Learning inverse folding from millions of predicted structures

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.372215Z

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Observation be00b58d-8103-46fb-b1a6-65451ca24d8b · outbound

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

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Learning from protein structure with geometric vector perceptrons

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Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.516693Z

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Observation ae1e4a57-c5d9-4986-b36f-2dfc1fa2a90b · outbound

This paper cites Basic local alignment search tool.Journal of Molecular Biology, 215(3):403–410, 1990.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Basic local alignment search tool.Journal of Molecular Biology, 215(3):403–410, 1990

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.338080Z

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Observation 249429ea-6f68-4404-8ab0-e02b1f930108 · outbound

This paper cites TM-align: a protein structure alignment algorithm based on the tm-score.Nucleic Acids Research, 33(7):2302–2309, 2005.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins TM-align: a protein structure alignment algorithm based on the tm-score.Nucleic Acids Research, 33(7):2302–2309, 2005

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.319044Z

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Observation 9b96d819-0184-4253-acd1-0abee1dc665a · outbound

This paper cites Fast and accurate protein structure search with Foldseek.Nature Biotechnology, 42(2):243–246, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Fast and accurate protein structure search with Foldseek.Nature Biotechnology, 42(2):243–246, 2024

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.296170Z

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Observation 7d6fb224-19af-4ba6-bf51-7ad9c479c973 · outbound

This paper cites VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning

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Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.550375Z

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Observation 93d21a52-5d66-41de-b79e-12f4edb493b7 · outbound

This paper cites an unresolved cited work.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:53:11.275331Z

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Observation acdd540a-508c-404b-846f-d4be399c0a1c · outbound

This paper cites BioPython: freely available python tools for computational molecular biology and bioinformatics.Bioinformatics, 25(11):1422, 2009.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins BioPython: freely available python tools for computational molecular biology and bioinformatics.Bioinformatics, 25(11):1422, 2009

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.257092Z

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Observation 3b52f3e5-ab65-4cc5-9e55-070a445438ea · outbound

This paper cites MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature Biotechnology, 35(11):1026–1028, 2017.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.Nature Biotechnology, 35(11):1026–1028, 2017

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Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.571102Z

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Observation 7fdb4247-6985-465d-a5f8-5cc9982636e0 · outbound

This paper cites an unresolved cited work.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:53:11.224888Z

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Observation 8e54af15-a0cc-4019-b834-29b1db0f055d · outbound

This paper cites Decoupled Weight Decay Regularization.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Decoupled Weight Decay Regularization

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.584618Z

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Observation 6e5058f6-0ac5-4914-b400-744e8d4bb0cd · outbound

This paper cites Evaluating protein transfer learning with TAPE.Advances in Neural Information Processing Systems, 32, 2019.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Evaluating protein transfer learning with TAPE.Advances in Neural Information Processing Systems, 32, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.208233Z

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Observation 07977bc8-5694-4c21-859f-434f116c9eaa · outbound

This paper cites ProteinNet: a standardized data set for machine learning of protein structure.BMC Bioinformatics, 20:1–10, 2019.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins ProteinNet: a standardized data set for machine learning of protein structure.BMC Bioinformatics, 20:1–10, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.187969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 771a964f-bdd0-4df6-829a-a066c24fc9c3 · outbound

This paper cites PEER: A comprehensive and multi-task benchmark for protein sequence understanding.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins PEER: A comprehensive and multi-task benchmark for protein sequence understanding

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.167652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6f395a68-438e-4cd2-bcde-9626b986befe · outbound

This paper cites PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications.Journal of Cheminformatics, 16(1):92, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications.Journal of Cheminformatics, 16(1):92, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.148879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f02469a6-f0d8-41d6-b85a-2899190fce20 · outbound

This paper cites ProteinGLUE multi-task benchmark suite for self-supervised protein modeling.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins ProteinGLUE multi-task benchmark suite for self-supervised protein modeling

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.121267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 41998c09-0ed2-4de5-87d7-7f4a8120ea07 · outbound

This paper cites DeepLoc: prediction of protein subcellular localization using deep learning.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins DeepLoc: prediction of protein subcellular localization using deep learning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.095937Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d24de8f1-40c4-49ce-adc1-bc96eccb8d61 · outbound

This paper cites DeepSol: a deep learning framework for sequence-based protein solubility prediction.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins DeepSol: a deep learning framework for sequence-based protein solubility prediction

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.070549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72401836-fdf9-4a7f-855a-3915b11442b5 · outbound

This paper cites FLIP: Benchmark tasks in fitness landscape inference for proteins.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins FLIP: Benchmark tasks in fitness landscape inference for proteins

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.047544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1d6ee837-c069-4f4b-8504-2dd113ddb297 · outbound

This paper cites ProteinShake: Building datasets and benchmarks for deep learning on protein structures.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins ProteinShake: Building datasets and benchmarks for deep learning on protein structures

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.023608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 02f48977-f3f3-4c00-aa23-5fbc2fb991c7 · outbound

This paper cites Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:11.001266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5fb65a95-cd70-4ee6-8c85-46f8f1518c42 · outbound

This paper cites Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.Nature Methods, 17(2):184–192, 2020.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.Nature Methods, 17(2):184–192, 2020

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.665114Z

Source-reported events for the cited work

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Observation e638c03b-743d-49ed-af62-8f10d26dc6df · outbound

This paper cites DIPS-plus: The enhanced database of interacting protein structures for interface prediction.Scientific Data, 10(1):509, 2023.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins DIPS-plus: The enhanced database of interacting protein structures for interface prediction.Scientific Data, 10(1):509, 2023

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:10.964896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6de9e84c-7f6d-4d4a-87a4-56b882374b6e · outbound

This paper cites A comprehensive dataset of protein-protein interactions and ligand binding pockets for advancing drug discovery.Scientific Data, 11(1):402, 2024.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins A comprehensive dataset of protein-protein interactions and ligand binding pockets for advancing drug discovery.Scientific Data, 11(1):402, 2024

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:10.931345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a42f59df-ff1e-4bef-9ec1-33d030fcbcfb · outbound

This paper cites The PDBbind database: methodologies and updates.Journal of Medicinal Chemistry, 48(12):4111–4119, 2005.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins The PDBbind database: methodologies and updates.Journal of Medicinal Chemistry, 48(12):4111–4119, 2005

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.683165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09aaa3c4-c990-4a4d-b417-dcc080486072 · outbound

This paper cites ATOM3D: Tasks On Molecules in Three Dimensions.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins ATOM3D: Tasks On Molecules in Three Dimensions

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T20:53:10.690259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f541a08b-7abd-4cdd-868c-51e4dd11b845 · outbound

This paper cites Task” indicates evaluation scope: “All.

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins Task” indicates evaluation scope: “All

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:53:10.889020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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