Author

Joelle N. Eaves

Michigan State UniversityORCID 0000-0002-5918-5279Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:graph neural network· 1 Organism:human· 1

Frequent Co-Authors

Daniel R. WoldringiD· 2 shared Mehrsa MardikoraemiD· 2 shared Nathaniel PascualiD· 2 shared Alexander Aljets· 1 shared Anton MahamaiD· 1 shared Benjamin J. OrlandoiD· 1 shared Bruno HagenbuchiD· 1 shared Erik M. ShapiroiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioengineering

Daniel R. WoldringORCID

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2 papers

Recent·Most cited

BioengineeringJournal of CheminformaticsPeer-reviewedMay 5, 2025

Predicting Inhibitors of OATP1B1 via Heterogeneous OATP-Ligand Interaction Graph Neural Network (HOLIgraph)

Mehrsa Mardikoraem, Joelle N. Eaves, Theodore Belecciu…·Daniel R. Woldring

This paper introduces HOLIgraph, a graph neural network model that predicts OATP1B1 inhibitors by integrating ligand features and protein-ligand interactions, achieving over 90% balanced accuracy.

2 citations

humanproteomics

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BioinformaticsbioRxivPreprintOct 2, 2024

EvoSeq-ML: Advancing Data-Centric Machine Learning with Evolutionary-Informed Protein Sequence Representation and Generation

Mehrsa Mardikoraem, Nathaniel Pascual, Joelle N. Eaves…·Daniel Woldring

This paper evaluates an ancestral sequence reconstruction-informed data augmentation strategy for improving protein sequence generation and representation learning, showing improved thermostability in generated variants.

DOI 10.1101/2024.10.02.616302

protein sequencestatistical model

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