Paper Citation Record · LEDGER

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation

As of 10 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2506.16921.

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

pith.paper-citation-record.v1
2506.16921 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:42:06.073288Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

36 of 36 outbound references displayed

verified exact14
verified fuzzy10
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3e5a0539-3db9-49c1-bc35-9de88ee7a399 · outbound

This paper cites Pervasive cooperative mutational effects on multiple catalytic enzyme traits emerge via long-range conformational dynamics.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Pervasive cooperative mutational effects on multiple catalytic enzyme traits emerge via long-range conformational dynamics

Reference 1

Resolution: verified exact; doi, observed 2026-08-06T23:42:09.259252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ea8d7ea-d3d8-4a46-91bc-86af2a23af8b · outbound

This paper cites Machine learning to navigate fitness landscapes for protein engineer- ing.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Machine learning to navigate fitness landscapes for protein engineer- ing

Reference 2

Resolution: malformed identifier; no resolver link, observed 2026-08-06T23:42:03.140128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9992cf3e-edf9-47dd-9bc0-da1a2670e93b · outbound

This paper cites Protein engineering in the deep learning era.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Protein engineering in the deep learning era

Reference 3

Resolution: verified exact; doi, observed 2026-08-06T23:42:09.028012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 21b9be84-b98f-4059-8353-0f1233bb0fc4 · outbound

This paper cites In: Currin A, Swainston N, editors.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation In: Currin A, Swainston N, editors

Reference 4

Resolution: verified exact; doi, observed 2026-08-06T23:42:08.794757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a5e2f9b-d114-4581-8707-3a6ffbaee389 · outbound

This paper cites From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineering.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineering

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T23:42:10.214752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ff044c67-c90f-408e-b8dc-0e563301732b · outbound

This paper cites Learning Epistasis and Residue Coevolution Patterns: Current Trends and Future Perspectives for Advancing Enzyme Engineering.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Learning Epistasis and Residue Coevolution Patterns: Current Trends and Future Perspectives for Advancing Enzyme Engineering

Reference 6

Resolution: verified exact; doi, observed 2026-08-06T23:42:08.632674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 933a5062-e922-4f55-b15b-fe3521901f7e · outbound

This paper cites Exploring protein fitness landscapes by directed evolution.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Exploring protein fitness landscapes by directed evolution

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:03.656672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c69c11b-c28f-44cb-b9ba-94c9c60cd93c · outbound

This paper cites A review on multiple sequence alignment from the perspective of genetic algorithm.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A review on multiple sequence alignment from the perspective of genetic algorithm

Reference 8

Resolution: verified exact; doi, observed 2026-08-06T23:42:08.392819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7ea4bb77-13c8-4bdb-92bf-040468bb0f06 · outbound

This paper cites VISUALIZING FITNESS LANDSCAPES.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation VISUALIZING FITNESS LANDSCAPES

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:12.607793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2e7e73f6-847c-41a3-8d5c-0e09a79ca943 · outbound

This paper cites Learning the pattern of epistasis linking genotype and phenotype in a protein.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Learning the pattern of epistasis linking genotype and phenotype in a protein

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:04.091026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cc49605-238b-449d-b113-94523ca6cd9e · outbound

This paper cites A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes

Reference 11

Resolution: verified exact; doi, observed 2026-08-06T23:42:08.152985Z

Source-reported events for the cited work

correction dated 2021-04-12. Source: crossref record 10.1038/s41598-021-86884-x->10.1038/s41598-018-35033-y:correction, observed 2026-07-11T03:09:49.715478+00:00. This notice travels one citation hop only.

Observation 36df1f5b-bcb6-4623-b01b-2afbac42921a · outbound

This paper cites Potts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Potts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:04.369737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88559d12-028a-416d-97f0-5b87ad77c7d4 · outbound

This paper cites Low-N protein engineering with data-efficient deep learning.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Low-N protein engineering with data-efficient deep learning

Reference 13

Resolution: verified exact; doi, observed 2026-08-06T23:42:07.950739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b013c521-fda5-4df9-ac73-0346488787c4 · outbound

This paper cites Learning protein fitness models from evolutionary and assay- labeled data.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Learning protein fitness models from evolutionary and assay- labeled data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:04.639698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c73ac5d-633c-48a9-b3bd-2cae45357c44 · outbound

This paper cites Higher-orderepistasisandphenotypic prediction.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Higher-orderepistasisandphenotypic prediction

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T23:42:07.697244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dbd242af-ad46-416e-b290-4c24d091880d · outbound

This paper cites A Gentle Introduction to Graph Neural Networks.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A Gentle Introduction to Graph Neural Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:04.924842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ed902f5-c95c-4c2c-abbb-dced7450606d · outbound

This paper cites Graph Neural Networks and Their Current Applications in Bioinformatics.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Graph Neural Networks and Their Current Applications in Bioinformatics

Reference 17

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T23:42:09.880935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bfa9e8b7-63e6-44ff-9e86-ad6cc81d0d4a · outbound

This paper cites ProS-GNN: Predicting effects of mutations on protein stability using graph neural networks.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation ProS-GNN: Predicting effects of mutations on protein stability using graph neural networks

Reference 18

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T23:42:09.646588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1183b1c4-9675-41cf-bf32-c3f620a685ac · outbound

This paper cites Quantitative exploration of the catalytic landscape separating divergent plant sesquiterpene synthases.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Quantitative exploration of the catalytic landscape separating divergent plant sesquiterpene synthases

Reference 19

Resolution: verified exact; doi, observed 2026-08-06T23:42:07.404749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 66d9f9ae-00c6-4f4a-af4b-357b37a6fa2f · outbound

This paper cites Biosynthetic potential of sesquiterpene synthases: product profiles of Egyptian Henbane premnaspirodiene synthase and related mutants.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Biosynthetic potential of sesquiterpene synthases: product profiles of Egyptian Henbane premnaspirodiene synthase and related mutants

Reference 20

Resolution: verified exact; doi, observed 2026-08-06T23:42:07.169304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6efc2f2d-7611-442d-bc99-7ba24a93e023 · outbound

This paper cites In: Sikosek T, editor.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation In: Sikosek T, editor

Reference 21

Resolution: verified exact; doi, observed 2026-08-06T23:42:06.830105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 29910b70-4358-42bb-9235-77eac260436f · outbound

This paper cites Wavelets: Mathematical Theory.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Wavelets: Mathematical Theory

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:12.352523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 13f26305-e1b5-43ac-9804-671a3b41a16f · outbound

This paper cites A wavelet tour of signal processing.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A wavelet tour of signal processing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:12.117342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 492379e6-0bf3-47b1-b895-18343356a329 · outbound

This paper cites A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:05.944234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1cd0efc-2210-49ad-8854-9fc293ad1a39 · outbound

This paper cites 4.2 - Multiscale Image Decompositions and Wavelets.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation 4.2 - Multiscale Image Decompositions and Wavelets

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:11.820051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d5a473ae-9098-49c9-bec4-f6189fc58569 · outbound

This paper cites A New Wavelet Threshold Determination Method Considering Interscale Correlation in Signal Denoising.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A New Wavelet Threshold Determination Method Considering Interscale Correlation in Signal Denoising

Reference 26

Resolution: verified exact; doi, observed 2026-08-06T23:42:06.525127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 49853f6a-c57f-4cc4-8adf-705ca5068ba4 · outbound

This paper cites Ideal spatial adaptation by wavelet shrinkage.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Ideal spatial adaptation by wavelet shrinkage

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:11.573676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1e8b0c12-9612-4df9-92d4-baec600a087f · outbound

This paper cites Mechanisms of DNA damage, repair, and mutagenesis.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Mechanisms of DNA damage, repair, and mutagenesis

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:11.368667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7b71fc80-f20b-4c1d-9b4b-b51ba8998757 · outbound

This paper cites Mutation, repair and recombination.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Mutation, repair and recombination

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:11.246533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ca0772a1-0773-4590-a67b-0c41c96ab82a · outbound

This paper cites The Context-Dependence of Mutations: A Linkage of Formalisms.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation The Context-Dependence of Mutations: A Linkage of Formalisms

Reference 30

Resolution: verified exact; doi, observed 2026-08-06T23:42:06.265273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3ef48e6d-ae34-4971-bed4-f67da6462abf · outbound

This paper cites A new model for learning in graph domains.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A new model for learning in graph domains

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:10.995504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3c57ae9a-1ff0-4552-850a-b3b6794b6729 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Semi-Supervised Classification with Graph Convolutional Networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:10.758326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 50a5c40d-617e-4c59-ac07-0cbe265aed40 · outbound

This paper cites A Flexible Generative Framework for Graph-based Semi-supervised Learning.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation A Flexible Generative Framework for Graph-based Semi-supervised Learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:10.550507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0a83f40f-f76e-44a4-8a21-68447e1603c1 · outbound

This paper cites The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:06.068058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c3226cc-dbf1-4fa0-979f-0fbe0738976c · outbound

This paper cites Minimum epistasis interpolation for sequence-function relationships.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation Minimum epistasis interpolation for sequence-function relationships

Reference 35

Resolution: verified exact; doi, observed 2026-08-06T23:42:06.145552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59607891-baf9-4b55-a6fd-065672e9a4c6 · outbound

This paper cites https://academic.oup.com/evolut/article- pdf/65/6/1544/47949872/evolut1544.pdf.

EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation https://academic.oup.com/evolut/article- pdf/65/6/1544/47949872/evolut1544.pdf

Reference 1558

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:03.955829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.