Author

Peter Tu

GE Global Research (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

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Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:multiome· 1 Approach:statistical model· 1

Frequent Co-Authors

Alison Caron· 1 shared Andrew Burns· 1 shared Azar AlizadehiD· 1 shared Brian Davis· 1 shared Christine SurretteiD· 1 shared Chrystal M. ChadwickiD· 1 shared Eric D. Williams· 1 shared Ernest FraenkeliD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alison Caron

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1 paper

Recent·Most cited

Integration of Multiomic and Multi-phenotypic Data Identifies Biological Pathways Associated with Physical Fitness

Azar Alizadeh, John F. Graf, Matthew J. Misner, Andrew Burns, Fiona Ginty, Kevin J. O’Donovan, J. Kenneth Wickiser, N Barringer, Gregory M Freisinger, Neil Hermansen, J. Elizabeth McDonough, Brian Davis, Evelina Loghin, Christine Surrette, Peter Tu, , Luca Marinelli

This paper introduces PhenoMol, a framework that integrates multiomic and multi-phenotypic data to identify biological pathways linked to physical fitness, outperforming traditional regression models.

Communications Biology · Feb 17, 2026Peer-reviewedBioinformatics