Author

Graham A. Colditz

Washington University in St. LouisORCID 0000-0002-7307-0291Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Organism:human· 3 Approach:statistical model· 3 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Assay:electronic health records· 1

Frequent Co-Authors

E. Shelley HwangiD· 2 shared Alla Y. KarpovaiD· 1 shared Anand S. MehtaiD· 1 shared André Luiz N. Targino da Costa· 1 shared Andrea L. BredemeyeriD· 1 shared Andrew HoustoniD· 1 shared Andrew T. ShinkleiD· 1 shared Austin N. Southard-SmithiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersPathology

E. Shelley HwangORCID

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Author profile →

3 papers

Recent·Most cited

PathologybioRxivPreprintJul 21, 2026

Extracellular Matrix Proteomic Signatures Associate with Disease-Free Survival in Later Events of Ductal Carcinoma In Situ or Invasive Breast Cancer

Taylor S. Hulahan, Laura Spruill, Bryn E. Gerding…·Peggi M. Angel

The paper identifies ECM proteomic signatures associated with disease-free survival in DCIS and IBC, showing reduced collagen peptides correlate with poorer outcomes.

DOI 10.64898/2026.07.16.738889

humanproteomics

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Cancer BiologyNature CancerPeer-reviewedOct 30, 2024

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Michael D. Iglesia, Reyka G. Jayasinghe, Siqi Chen…·Li Ding

This study identifies breast cancer subtypes and their lineage origins by analyzing chromatin accessibility and transcriptional dynamics using multi-omic techniques.

47 citationstop 2%

humanbulk RNA-seq

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BioinformaticsJournal of the Royal Statistical Society Series C (Applied Statistics)Peer-reviewedNov 7, 2020

Functional Ensemble Survival Tree: Dynamic Prediction of Alzheimer's Disease Progression Accommodating Multiple Time-Varying Covariates

Shu Jiang, Yijun Xie, Graham A. Colditz

The paper develops a functional ensemble survival tree framework to predict Alzheimer's disease progression using time-varying biomarkers and baseline covariates, showing good performance in simulations and ADNI data.

28 citations

humanelectronic health records

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