Author

Jamie J. R. Bennett

Icahn School of Medicine at Mount SinaiORCID 0000-0002-9748-5010Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cell Biology· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:imputation· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Alan D. SterniD· 1 shared Chenyu LiuiD· 1 shared Gabriel E. HoffmaniD· 1 shared Gaurav Shankar PandeyiD· 1 shared Georgios VoloudakisiD· 1 shared Marc R. BirtwistleiD· 1 shared Marios AnyfantakisiD· 1 shared Panos RoussosiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperCell Biology

Alan D. SternORCID

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2 papers

Recent·Most cited

Genetic & Genomic MedicineBioinformaticsPeer-reviewedSep 30, 2026

✦ In-depth digest

GROMTools: scalable individual-level GReX imputation for mega-biobank-scale cohorts

Marios Anyfantakis, Sanan Venkatesh, Jamie J. R. Bennett…·Georgios Voloudakis

GROMTools, a sparse-weight C++/R engine streaming PLINK2 genotypes, reproduces PrediXcan and PLINK2 GReX imputations with about 100-fold less CPU time and 33-fold less peak memory.

DOI 10.1093/bioinformatics/btag719

humanbulk RNA-seq

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Cell Biologynpj Systems Biology and ApplicationsPeer-reviewedJun 4, 2024

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events

Jamie J. R. Bennett, Alan D. Stern, Xiang Zhang…·Gaurav Shankar Pandey

This study uses machine learning to predict cell division from ERK and Akt activity dynamics in single cells, finding ERK dynamics more predictive than Akt.

8 citations

humanscRNA-seq

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