Author

David Kozono

Brigham and Women's HospitalORCID 0000-0002-8916-396XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:drug response / drug discovery· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Ann L. ObergiD· 1 shared Christopher J. GraseriD· 1 shared Cindy Lin· 1 shared Franziska Michor AiD· 1 shared G. F. MoorheadiD· 1 shared Galit LahaviD· 1 shared Hua LuiD· 1 shared Jamie DeaniD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Ann L. ObergORCID

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2 papers

Recent·Most cited

Mechanistic modeling and machine learning identifies optimum radiotherapy schedules to prevent treatment-induced metastasis

Christopher J. Graser, Zhi Zhou, Manuel Schürch, G. F. Moorhead, Justin Dean, Cindy Lin, Jamie Dean, David Kozono, Galit Lahav, Franziska Michor A

The paper identifies optimal radiotherapy schedules to reduce metastasis by combining mechanistic modeling and machine learning with in silico clinical trials.

bioRxiv · Jul 2, 2025 · PreprintBioinformatics

Identify Non-Mutational p53 Functional Deficiency in Human Cancers

Qianpeng Li, Yang Zhang, Sicheng Luo, Zhang Zhang, Ann L. Oberg, David Kozono, Hua Lu, Jann Nagina Sarkaria, Lina Ma, Liguo Wang

The paper identifies non-mutational p53 functional deficiency in TP53 wild-type tumors using SVM models, revealing significant functional impairment and clinical implications.

Genomics Proteomics & Bioinformatics · Sep 26, 2024Peer-reviewedBioinformatics