Author

R. Krishna Murthy Karuturi

The JAX Cancer Center

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 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Carol J. BultiD· 1 shared Carolyn A. PaisieiD· 1 shared Charles LeeiD· 1 shared Chengsheng ZhangiD· 1 shared Edison T. LiuiD· 1 shared Eliza CerveiraiD· 1 shared Francesca MenghiiD· 1 shared Guruprasad AnandaiD· 1 shared

Activity by Year

2018-2018 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperCancer Biology

Carol J. BultORCID

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2 papers

Recent·Most cited

Pan-cancer machine learning predictors of primary site of origin and molecular subtype

William F. Flynn, Sandeep Namburi, Carolyn A. Paisie, Honey V. Reddi, Sheng Li, R. Krishna Murthy Karuturi, Joshy George

This paper develops machine learning models to predict the primary site of origin and molecular subtype of metastatic cancers using gene expression data from TCGA, achieving high accuracy across multiple cancer types.

bioRxiv · Jul 5, 2018 · PreprintBioinformatics

Evolution of an intratumoral ecology susceptible to successive treatment in breast cancer xenografts

Hyunsoo Kim, Pooja Kumar, Francesca Menghi, Javad Noorbakhsh, Eliza Cerveira, Mallory Ryan, Qihui Zhu, Guruprasad Ananda, Joshy George, Henry C. Chen, Susan Mockus, Chengsheng Zhang, Yan Yang, James Keck, R. Krishna Murthy Karuturi, , Jeffrey H. Chuang

This study quantifies intratumoral subclone dynamics in breast cancer xenografts, revealing a treatable ecology where subclone ratios predict treatment response.

bioRxiv · Jan 18, 2018 · PreprintCancer Biology