Author

Tyler Matsuzaki

Massachusetts Institute of TechnologyORCID 0009-0008-4720-3493Unclaimed ORCID profile · follow to get notified of new preprints

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Tyler Matsuzaki1 paper

Biology Disciplines

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Systems Biology· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Douglas A. LauffenburgeriD· 2 shared Linda Gay GriffithiD· 2 shared Nikolaos MeimetisiD· 2 shared Erin N. TevonianiD· 1 shared Jose L. CadavidiD· 1 shared Lindsey FosteriD· 1 shared Xingrui MouiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

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7 top collaborators · 17 mutual co-author links

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2 shared papersSystems Biology

Douglas A. LauffenburgerORCID

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2 papers

Recent·Most cited

Systems BiologybioRxivPreprintOct 27, 2026

Interactome-based deep learning and path-level decomposition reveal TGFβ-IFNα competition in MASH

Nikolaos Meimetis, Tyler Matsuzaki, Xingrui Mou…·Douglas A. Lauffenburger

The paper uses a deep learning framework to analyze drug-induced transcriptomics and identifies a four-node module involved in TGFβ-IFNα competition in MASH.

DOI 10.64898/2026.10.24.761530

humanbulk RNA-seq

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Systems BiologybioRxivPreprintJan 17, 2025

Systems biology framework for rational design of operational conditions for in vitro / in vivo translation of microphysiological systems

Jose L. Cadavid, Nikolaos Meimetis, Tyler Matsuzaki…·Douglas A. Lauffenburger

The paper develops a machine learning framework to identify optimal experimental conditions for improving the translatability of microphysiological systems to in vivo contexts, using MAFLD as a case study.

2 citations

humanmachine learning (classical)

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