Author

Yu Xia

The University of Melbourne

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

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Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Organism:human· 1 Assay:protein sequence· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Ansuman T. SatpathyiD· 1 shared Asela Hevapathige· 1 shared Bence DánieliD· 1 shared Chathura J. Gamage· 1 shared Damith SenanayakeiD· 1 shared Howard Y. ChangiD· 1 shared Ingrid Eileen SchefferiD· 1 shared James ZouiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBioinformatics

Ansuman T. SatpathyORCID

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2 papers

Recent·Most cited

Knowledge Inclusive Machine Learning for Disease Gene Prioritisation

Chathura J. Gamage, Yu Xia, Ravisha Rupasinghe, Sachith Seneviratne, Damith Senanayake, Tamasha Malepathirana, Asela Hevapathige, Mark Corbett, Terence John O'Brien, Steven Petrou, Samuel Frank Berkovic, Ingrid Eileen Scheffer, Jozef Gécz, Melanie Bahlo, Mark F. Bennett, Saman Kumara Halgamuge

This paper introduces KIML, a machine learning framework that integrates experimental data with biological knowledge to improve disease gene prioritisation, showing better performance than existing methods.

bioRxiv · May 17, 2026 · PreprintGenetics

TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-binding analyses

Kevin Wu, Kathryn E. Yost, Bence Dániel, Julia A. Belk, Yu Xia, Takeshi Egawa, Ansuman T. Satpathy, Howard Y. Chang, James Zou

TCR-BERT uses self-supervised transfer learning on unlabeled T-cell receptor sequences to learn representations that improve antigen-binding prediction, specificity clustering, and computational TCR sequence design.

bioRxiv · Nov 18, 2021 · PreprintBioinformatics