Author

Ruth T. Taniguchi

Adaptive Biotechnologies (United States)

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· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Organism:human· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:statistical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Harlan S. RobinsiD· 2 shared André FrankeiD· 1 shared Brittney Robinett· 1 shared Bryan Howie· 1 shared Gheath Alatrash· 1 shared Haiyin Chen‐HarrisiD· 1 shared Harus Jabran ZahidiD· 1 shared Hesham ElAbdiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersCancer Biology

Harlan S. RobinsORCID

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2 papers

Recent·Most cited

The Immune-Mutation Axis of Cancer Incidence: Insights from 30,000 TCRβ Repertoires

Harus Jabran Zahid, Matthew E. Lee, Ruth T. Taniguchi, Gheath Alatrash, Thomas McFall, Marco Garcia Noceda, Harlan S. Robins, Julia Greissl

The paper analyzes TCRβ repertoires from 30,000 individuals to show that immune decline with age correlates with cancer incidence, revealing an immune-mutation balance in carcinogenesis.

bioRxiv · Oct 21, 2024 · PreprintCancer Biology

Seq2MAIT: A Novel Deep Learning Framework for Identifying Mucosal Associated Invariant T (MAIT) Cells

Hesham ElAbd, Rachel Byron, Steven Woodhouse, Brittney Robinett, Joe Sulc, André Franke, Mitchell W. Pesesky, Wenyu Zhou, Haiyin Chen‐Harris, Bryan Howie, Ruth T. Taniguchi, Harlan S. Robins

Seq2MAIT identifies MAIT cells from bulk TCR-sequencing data using a transformer-based model, achieving AUROC >0.80 across datasets.

bioRxiv · Mar 12, 2024 · PreprintBioinformatics