Author

Vera Jean Suman

Mayo ClinicORCID 0000-0002-9640-5189Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:drug response / drug discovery· 3 Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:multiome· 1

Frequent Co-Authors

Judy Caroline BougheyiD· 3 shared Krishna R. KalariiD· 3 shared Liewei WangiD· 3 shared Matthew Philip GoetziD· 3 shared Kevin J. ThompsoniD· 2 shared Richard M. WeinshilboumiD· 2 shared Xiaojia TangiD· 2 shared Alaina N. LewisiD· 1 shared

Activity by Year

2018-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersBioinformatics

Judy Caroline BougheyORCID

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3 papers

Recent·Most cited

Patient-Derived Xenograft-Guided Prediction of Chemotherapy Response in Triple-Negative Breast Cancer

Jonathan Thomas Lei, Lacey Elizabeth Dobrolecki, Chen Lu Huang, Ramakrishnan Rajaram Srinivasan, Suhas V. Vasaikar, Alaina N. Lewis, Christina Sallas, Na Zhao, Jin Cao, John David Landua, Jacob B. Pilcher, Chang In Moon, Yuxing Liao, Susan Galloway Hilsenbeck, Mothaffar Fahed Rimawi, , Michael T. Lewis

This paper develops chemotherapy-specific predictors for triple-negative breast cancer using patient-derived xenografts and multi-omic data, achieving high AUROC scores for response prediction.

bioRxiv · Dec 9, 2024 · PreprintCancer Biology

OmicsFootPrint: a framework to integrate and interpret multi-omics data using circular images and deep neural networks

Xiaojia Tang, Naresh Prodduturi, Kevin J. Thompson, Richard M. Weinshilboum, Ciara Catherine O'Sullivan, Judy Caroline Boughey, Hamid R. Tizhoosh, Eric W. Klee, Liewei Wang, Matthew Philip Goetz, Vera Jean Suman, Krishna R. Kalari

OmicsFootPrint integrates and interprets multi-omics data using circular images and deep neural networks, achieving high AUC scores in cancer subtype classification and drug response prediction.

Nucleic Acids Research · Oct 6, 2024Peer-reviewedBioinformatics

PANOPLY: Omics-guided drug prioritization method tailored to an individual patient

Krishna R. Kalari, Jason P. Sinnwell, Kevin J. Thompson, Xiaojia Tang, Erin E. Carlson, Jia Yu, Peter T. Vedell, James N. Ingle, Richard M. Weinshilboum, Judy Caroline Boughey, Liewei Wang, Matthew Philip Goetz, Vera Jean Suman

PANOPLY prioritizes cancer drugs for individual patients using multi-omics data and machine learning, showing effectiveness in a chemotherapy-resistant tumor model.

JCO Clinical Cancer Informatics · Oct 15, 2018Peer-reviewedBioinformatics