Author

Kirsten R. McEwen

Imperial College LondonORCID 0000-0002-9173-5664Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Developmental Biology· 1 Molecular Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Organism:mouse· 3 Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Approach:Bayesian inference· 1 Research Focus:cell type annotation· 1 Approach:experimental assay· 1

Frequent Co-Authors

Michael P. H. StumpfiD· 2 shared Thalia E. Chan· 2 shared Alessandro SardiniiD· 1 shared Ananth V. Pallaseni· 1 shared Ann C. BabtieiD· 1 shared Bing LiangiD· 1 shared Chie NaruseiD· 1 shared Enrico G. PetrettoiD· 1 shared

Activity by Year

2018-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersMolecular Biology

Michael P. H. StumpfORCID

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3 papers

Recent·Most cited

Sex differences in gene expression and proliferation are dependent on the epigenetic modifier HP1γ

Pui Pik Law, Ping‐Kei Chan, Kirsten R. McEwen, Huihan Zhi, Bing Liang, Chie Naruse, Masahide Asano, KC Tan-Un, Gcf Chan, Richard Festenstein

The paper shows that HP1γ regulates sex differences in gene expression and proliferation in male and female mice by affecting autosomal gene expression.

bioRxiv · Mar 4, 2019 · PreprintDevelopmental Biology

Signalling pathways drive heterogeneity of ground state pluripotency

Kirsten R. McEwen, Sarah Linnett, Harry G. Leitch, Prashant Kumar Srivastava, Lara Al Zouabi, Tien-Chi Huang, Maxime Rotival, Alessandro Sardini, Thalia E. Chan, Sarah L. Filippi, Michael P. H. Stumpf, Enrico G. Petretto, Petra Hájková

This study shows that 2i conditions increase transcriptional heterogeneity in pluripotent stem cells, driven by signaling pathways and negative feedback loss.

bioRxiv · Aug 16, 2018 · PreprintMolecular Biology

Empirical Bayes Meets Information Theoretical Network Reconstruction from Single Cell Data

Thalia E. Chan, Ananth V. Pallaseni, Ann C. Babtie, Kirsten R. McEwen, Michael P.H. Stumpf

The paper introduces a method combining empirical Bayes and information theory to reconstruct gene regulatory networks from single-cell data, improving accuracy with prior information.

bioRxiv · Feb 13, 2018 · PreprintSystems Biology