Author

Nick Sexson

University of Florida

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3 Scientific Communication & Education· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 3 Research Focus:protein structure prediction· 3 Approach:statistical model· 3 Assay:protein structure· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Organism:E. coli· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

José Cleydson F. SilvaiD· 3 shared Layla A. SchusteriD· 2 shared Márcio F. R. ResendeiD· 2 shared Matias KirstiD· 2 shared Raquel DiasiD· 2 shared Raquel DiasiD· 2 shared Adilson Lopes· 1 shared Arthur Vieira· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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3 shared papersBioinformatics

José Cleydson F. SilvaORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

SpaceBio Knowledge Hub: A LiteratOmics Platform for Microgravity and Space Biology Research

Jose Cleydson F Silva, Arthur Vieira, Melinda S. Chue Donahey, Sirlane Maria do Carmo Silva, Tomas Veloso, Adilson Lopes, Nick Sexson, Richard Barker, David Marshall Porterfield, Carlos Alberto Silva, Raquel Dias

The paper introduces SpaceBio Knowledge Hub, an AI-driven platform for organizing and integrating space biology literature into a navigable knowledge landscape.

bioRxiv · Jul 14, 2026 · PreprintScientific Communication & Education

InteracTor: Feature Engineering and Explainable AI for Profiling Protein Structure-Interaction-Function Relationships

José Cleydson F. Silva, Layla A. Schuster, Nick Sexson, Melissa Erdem, Ryan Hulke, Matias Kirst, Márcio F. R. Resende, Raquel Dias

InteracTor extracts 3D structural interaction features and uses XAI to improve protein family classification beyond primary/secondary structure features.

PLoS Computational Biology · Oct 13, 2025Peer-reviewedBioinformatics

Limitations of Current Machine-Learning Models in Predicting Enzymatic Functions for Uncharacterized Proteins

Valérie de Crécy‐Lagard, Raquel Dias, Nick Sexson, Iddo Friedberg, Yifeng Yuan, Manal A. Swairjo

The paper evaluates machine-learning models' ability to predict enzymatic functions for uncharacterized proteins and finds they fail to integrate scientific reasoning and make logic errors.

G3 Genes Genomes Genetics · Jul 24, 2025Peer-reviewedBioinformatics

InteracTor: A new integrative feature extraction toolkit for improved characterization of protein structural properties

José Cleydson F. Silva, Layla A. Schuster, Nick Sexson, Matias Kirst, Márcio F. R. Resende, Raquel Dias

InteracTor extracts interatomic interaction features from protein 3D structures to improve characterization of structural properties and functional insights.

bioRxiv · Oct 7, 2024 · PreprintBioinformatics