Author

Kartik Subramanian

Harvard UniversityORCID 0000-0002-6900-8882Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:experimental assay· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1

Frequent Co-Authors

Peter Karl SorgeriD· 3 shared Caitlin E. MillsiD· 2 shared Clarence YappiD· 2 shared Mirra ChungiD· 2 shared Ajay PillaiiD· 1 shared Ajit J. NirmaliD· 1 shared Albert Lee· 1 shared Alexandra B. London· 1 shared

Activity by Year

2017-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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3 shared papersSystems Biology

Peter Karl SorgerORCID

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3 papers

Recent·Most cited

Systems BiologyNature CommunicationsPeer-reviewedNov 14, 2022

Multiplexed and reproducible high content screening of live and fixed cells using the Dye Drop method

Caitlin E. Mills, Kartik Subramanian, Marc A. Hafner…·Peter Karl Sorger

The paper introduces a method called Dye Drop for high-throughput single-cell assays in 384-well plates, enabling detailed dose-response analysis of small molecules in breast cancer cell lines.

34 citations

humanimaging

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Systems BiologyCommunications BiologyPeer-reviewedOct 7, 2022

A LINCS microenvironment perturbation resource for integrative assessment of ligand-mediated molecular and phenotypic responses

Sean M. Gross, Mark A. Dane, Rebecca Lee Smith…·Laura M. Heiser

The paper presents a LINCS Microenvironment perturbation dataset cataloging transcriptional, proteomic, epigenomic, and phenotypic responses of MCF10A cells to six ligands, enabling integrative analysis of molecular and phenotypic changes.

35 citations

humanbulk RNA-seq

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Systems BiologyMolecular Systems BiologyPeer-reviewedNov 1, 2017

From word models to executable models of signaling networks using automated assembly

Benjamin M. Gyori, John A. Bachman, Kartik Subramanian…·Peter Karl Sorger

The paper introduces INDRA, a tool that converts natural language descriptions of molecular mechanisms into executable computational models of biological networks.

180 citationstop 2%

statistical modelmachine learning (classical)

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