Author

Ian Ellis

Liverpool Womens NHS Foundation TrustPrimary ORCID profile (0000-0001-8035-6012 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Ian EllisiD1 paper · University of Dundee

Biology Disciplines

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Genetics· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Organism:mouse· 1 Approach:statistical model· 1 Research Focus:variant calling· 1

Frequent Co-Authors

A. Paul BevaniD· 1 shared Abhijit DixitiD· 1 shared Adam Hunter· 1 shared Adrian R. TiveyiD· 1 shared Alan DonaldsoniD· 1 shared Alan E Fryer· 1 shared Alejandro SifrimiD· 1 shared Alexandra S. NeaversoniD· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperGenetics

A. Paul BevanORCID

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2 papers

Recent·Most cited

Mouse and cellular models of KPTN-related disorder implicate mTOR signalling in cognitive and progressive overgrowth phenotypes

Maria O. Levitin, Lettie E. Rawlins, Gabriela Sánchez-Andrade, Osama A. Arshad, Stephan C. Collins, Stephen J. Sawiak, Philip H. Iffland, Malin H. L. Andersson, Caleb P. Bupp, Emma L. Cambridge, Eve L. Coomber, Ian Ellis, Johanna C. Herkert, Holly Ironfield, Logan Jory, , Sebastian S. Gerety

The paper investigates KPTN-related disorder using mouse and human stem cell models, identifying mTOR pathway dysregulation as a key mechanism underlying cognitive and overgrowth phenotypes.

bioRxiv · Jul 15, 2022 · PreprintGenetics

Prevalence, phenotype and architecture of developmental disorders caused by de novo mutation

Jeremy F. McRae, Stephen Clayton, Tomas W. Fitzgerald, Joanna Kaplanis, Elena Prigmore, Diana Rajan, Alejandro Sifrim, Stuart Aitken, Nadia A. Akawi, Mohsan Alvi, Kirsty Ambridge, Daniel M. Barrett, Tanya Bayzetinova, Philip Jones, Wendy D. Jones, , Neeti Ghali

The paper analyzes de novo mutations in developmental disorders using exome sequencing of 4,293 families, identifying 94 genes and estimating a birth prevalence of 0.22-0.47%.

bioRxiv · Mar 7, 2019 · PreprintGenetics