Author

Jeremy L. England

ORCID 0000-0002-3331-2583Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genomics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:perturbation response prediction· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Lena Granovsky· 2 shared Alon Gonen· 1 shared Ching-Hao WangiD· 1 shared Chris Lin· 1 shared Finnian Firth· 1 shared Gal Keinan· 1 shared Glyn Bradley· 1 shared Jiang Zhu· 1 shared

Activity by Year

2023-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersSystems Biology

Lena Granovsky

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2 papers

Recent·Most cited

Systems BiologybioRxivPreprintMar 20, 2023

Learning Perturbation-specific Cell Representations for Prediction of Transcriptional Response across Cellular Contexts

Gal Keinan, Karen Sayal, Alon Gonen…·Jeremy L. England

PerturbX predicts transcriptional responses to perturbations in new cellular contexts using deep learning trained on high-throughput screens.

DOI 10.1101/2023.03.20.533433

deep learningperturbation response prediction

GenomicsbioRxivPreprintJan 18, 2023

Simple Causal Relationships in Gene Expression Discovered through Deep Learned Collective Variables

Ching-Hao Wang, Kalin Vetsigian, Chris Lin…·Jeremy L. England

The paper develops a deep learning approach to identify simple causal relationships in gene expression by finding low-dimensional representations that predict genetic perturbation responses.

DOI 10.1101/2023.01.18.524617

bulk RNA-seqdeep learning