Author

Daniel F. O. Onah

UCL Queen Square Institute of NeurologyORCID 0000-0001-6192-6702Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Organism:mouse· 2 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Antonio Rueda Martin· 1 shared Arianna TucciiD· 1 shared Augusto RendoniD· 1 shared David ZhangiD· 1 shared Ellen M. McDonaghiD· 1 shared Henry HouldeniD· 1 shared John HardyiD· 1 shared Juan Antonio BotíaiD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

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10 top collaborators · 36 mutual co-author links

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1 shared paperGenetics

Antonio Rueda Martin

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJan 26, 2026

Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data

Daniel F. O. Onah, Maria De La Luz Lomboy Toledo

This study uses machine learning on single-cell RNA-seq data from mouse pancreatic islets to identify T2D-associated gene expression signatures.

DOI 10.64898/2026.01.23.701384

𝕏 PostBluesky

GeneticsbioRxivPreprintMar 27, 2018

G2P: Using machine learning to understand and predict genes causing rare neurological disorders

Juan Antonio Botía, Sebastian Guelfi, David Zhang…·Mina Ryten

The paper develops a machine learning model to predict genes causing rare neurological disorders and shows it accurately identifies disease-associated genes.

8 citations

mousemachine learning (classical)

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