Author

Boris Hartmann

Icahn School of Medicine at Mount SinaiORCID 0000-0002-5649-6776Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:cell-cell communication· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1

Frequent Co-Authors

Elena ZaslavskyiD· 3 shared Stuart C. SealfoniD· 3 shared Antonio CappuccioiD· 1 shared Chad L. MyersiD· 1 shared Daniil Kudrin· 1 shared German NudelmaniD· 1 shared Irina Nudelman· 1 shared Maria D. ChikinaiD· 1 shared

Activity by Year

2019-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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3 shared papersBioinformatics

Elena ZaslavskyORCID

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3 papers

Recent·Most cited

Comparing host module activation patterns and temporal dynamics in infection by influenza H1N1 viruses

Irina Nudelman, Daniil Kudrin, German Nudelman, Raamesh Deshpande, Boris Hartmann, Steven H. Kleinstein, Chad L. Myers, Stuart C. Sealfon, Elena Zaslavsky

This study compares host module activation patterns and temporal dynamics across four influenza H1N1 viruses to identify conserved and differentially regulated immune responses.

Frontiers in Immunology · Jul 14, 2021Peer-reviewedBioinformatics

Deciphering the combinatorial interaction landscape

Antonio Cappuccio, Shane T. Jensen, Boris Hartmann, Stuart C. Sealfon, Vassili Soumelis, Elena Zaslavsky

The paper introduces SAIL, a machine learning tool to predict and analyze combinatorial stimulus interactions, revealing context-dependent functions and probabilistic algebra of cellular responses.

bioRxiv · Oct 3, 2019 · PreprintBioinformatics

Pathway-Level Information ExtractoR (PLIER) for gene expression data

Weiguang Mao, Elena Zaslavsky, Boris Hartmann, Stuart C. Sealfon, Maria D. Chikina

PLIER improves pathway inference and cell proportion analysis in gene expression data, enhancing replicability and biological insight in trans-eQTL studies.

Nature Methods · Jun 27, 2019Peer-reviewedGenomics