Author

Zoubin Ghahramani A

University of CambridgeORCID 0000-0002-7464-6475Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Developmental Biology· 1

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Anastasiya SybirnaiD· 2 shared Christopher A. PenfoldiD· 2 shared John E. ReidiD· 2 shared Lorenz WernischiD· 2 shared M. Azim SuraniiD· 2 shared Murray GrantiD· 2 shared Yun HuangiD· 2 shared Aracely Castillo-VenzoriD· 1 shared

Activity by Year

2018-2018 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 36 mutual co-author links

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2 shared papersDevelopmental Biology

Anastasiya SybirnaORCID

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2 papers

Recent·Most cited

Bayesian inference of transcriptional branching identifies regulators of early germ cell development in humans

Christopher A. Penfold, Anastasiya Sybirna, John E. Reid, Aracely Castillo-Venzor, Elena Drousioti, Yun Huang, Murray Grant, Lorenz Wernisch, Zoubin Ghahramani A, M. Azim Surani

This paper develops a Bayesian pseudotime method to model transcriptional branching in human embryos and identifies regulators of PGC specification.

bioRxiv · Oct 15, 2018 · PreprintDevelopmental Biology

Branch-recombinant Gaussian processes for analysis of perturbations in biological time series

Christopher A. Penfold, Anastasiya Sybirna, John E. Reid, Yun Huang, Lorenz Wernisch, Zoubin Ghahramani A, Murray Grant, M. Azim Surani

This paper introduces branch-recombinant Gaussian processes (B-RGPs) to analyze branching and recombination in biological time series, demonstrating their application to gene expression data in Arabidopsis thaliana.

Bioinformatics · Jul 5, 2018Peer-reviewedBioinformatics