Author

Alexander van Oudenaarden

Primary ORCID profile (0000-0002-9442-3551 · 31 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Alexander van OudenaardeniD31 papers · Royal Netherlands Academy of Arts and Sciences

Biology Disciplines

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Systems Biology· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:clustering· 2 Research Focus:differential expression· 2 Organism:mouse· 2 Assay:scRNA-seq· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Stefan SemrauiD· 3 shared Magali Soumillon· 2 shared Bogdan BudnikiD· 1 shared Davide Cacchiarelli· 1 shared Edoardo Airoldi· 1 shared Johanna Goldmann· 1 shared Nikolai SlavoviD· 1 shared Rudolf Jaenisch· 1 shared

Activity by Year

2014-2016 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersSystems Biology

Stefan SemrauORCID

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3 papers

Recent·Most cited

Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells

Stefan Semrau, Johanna Goldmann, Magali Soumillon, Tarjei S. Mikkelsen, Rudolf Jaenisch, Alexander van Oudenaarden

This study uses single-cell transcriptomics to analyze lineage commitment in differentiating mouse embryonic stem cells, identifying key transcriptional changes and a phase of susceptibility to lineage signals.

bioRxiv · Aug 7, 2016Systems Biology

Differential stoichiometry among core ribosomal proteins

Nikolai Slavov, Stefan Semrau, Edoardo Airoldi, Bogdan Budnik, Alexander van Oudenaarden

This study quantifies core ribosomal protein stoichiometry in mouse embryonic stem cells and yeast, showing variability influenced by growth conditions and ribosome-mRNA binding.

bioRxiv · Sep 19, 2015Systems Biology

Characterization of directed differentiation by high-throughput single-cell RNA-Seq

Magali Soumillon, Davide Cacchiarelli, Stefan Semrau, Alexander van Oudenaarden, Tarjei S Mikkelsen

The paper develops a single-cell RNA-Seq protocol to analyze adipogenic differentiation and finds an inverse relationship between inflammatory gene expression and lipid accumulation in human cells.

bioRxiv · Mar 5, 2014 · PreprintGenomics