Author

Eileen Mary Boyle

NYU Langone HealthORCID 0000-0001-8791-1744Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:experimental assay· 1

Frequent Co-Authors

Ahmet DoǧaniD· 2 shared Benjamin T. DiamondiD· 2 shared Even Holth Rustad· 2 shared Francesco MauraiD· 2 shared Gareth John MorganiD· 2 shared Kylee H. MaclachlaniD· 2 shared Malin L. HultcrantziD· 2 shared Niccolò BolliiD· 2 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenomics

Ahmet DoǧanORCID

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3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintFeb 26, 2025

Single-cell profiling of human bone marrow reveals multiple myeloma progression is accompanied by an increase in CD56bright bone marrow resident NK cells.

Elise Rees, Isabella Sodi, Kane A. Foster…·Kwee Yong

The paper shows that multiple myeloma progression is linked to increased CD56bright bone marrow resident NK cells, which may contribute to immune evasion.

2 citations

humanscRNA-seq

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GenomicsNature CommunicationsPeer-reviewedAug 27, 2021

Copy number signatures predict chromothripsis and associate with poor clinical outcomes in patients with newly diagnosed multiple myeloma

Kylee H. Maclachlan, Even Holth Rustad, Andriy Derkach…·Francesco Maura

This study shows copy number signatures predict chromothripsis in multiple myeloma and link to poor clinical outcomes using whole genome and exome sequencing data.

49 citationstop 3%

humanwhole-genome sequencing

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GenomicsbioRxivPreprintDec 18, 2019

Revealing the impact of recurrent and rare structural variants in multiple myeloma

Even Holth Rustad, Venkata D. Yellapantula, Dominik Głodzik…·Francesco Maura

This study identifies 100 SV hotspots and 31 new candidate driver genes in multiple myeloma, revealing that 63% of SVs remain unexplained and are associated with outlier gene expression.

5 citations

humanwhole-genome sequencing

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