Author

John A. Martignetti

Icahn School of Medicine at Mount Sinai

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 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Alesia AntoineiD· 1 shared Arpit DaveiD· 1 shared Brandon R. Bruhn· 1 shared Eric E. SchadtiD· 1 shared Ethan Ellis· 1 shared Fan YangiD· 1 shared Hanane Arib· 1 shared Hardik ShahiD· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperGenomics

Alesia AntoineORCID

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2 papers

Recent·Most cited

Insights into impact of DNA copy number alteration and methylation on the proteogenomic landscape of human ovarian cancer via a multi-omics integrative analysis

Xiaoyu Song, Jiayi Ji, Kevin J. Gleason, Fan Yang, John A. Martignetti, Lin Chen, Pei Wang

The paper introduces iProFun, a multi-omics tool to identify DNA copy number and methylation effects on proteogenomic traits in ovarian cancer, finding 500 and 122 genes with cis-associations.

Molecular & Cellular Proteomics · Jun 21, 2019Peer-reviewedBioinformatics

Multiparameter cell characterization using nanofluidic technology facilitates real-time phenotypic and genotypic elucidation of intratumor heterogeneity

Kristin G. Beaumont, Wissam Hamou, Nenad Bozinovic, Thomas R. Silvers, Hardik Shah, Arpit Dave, Kimaada Allette, Maya Strahl, Ying‐Chih Wang, Hanane Arib, Alesia Antoine, Ethan Ellis, Melissa Laird Smith, Brandon R. Bruhn, Peter Remsen Dottino, , Robert Sebra

The paper uses a nanofluidic platform to enable single-cell phenotypic and genetic profiling of ovarian cancer cells, revealing clonal diversity and TP53 mutation patterns associated with tumor heterogeneity.

bioRxiv · Oct 31, 2018 · PreprintGenomics