The van Oudenaarden lab is using a combination of experimental, computational, and theoretical approaches to quantitatively understand decision‐making in single cells with a focus on questions in developmental and stem cell biology. We are particularly interested in how cells use gene networks to make robust decisions even in the presence of significant fluctuations in gene expression.
About the research
Key publications (5 recent)
S. S. Dey, L. Kester, B. Spanjaard, M. Bienko, and A. van Oudenaarden
Integrated genome and transcriptome sequencing of the same cell
Nature Biotechnology doi: 10.1038/nbt.3129 (2015).
J. P. Junker, E. S. Noel, V. Guryev, K. A. Peterson, G. Shah, J. Huisken, A. P. McMahon, E. Berezikov, J. Bakkers, and A. van Oudenaarden
Genome-wide RNA tomography in the zebrafish embryo
Cell 159, 662 – 675 (2014).
D. Grün, L. Kester, and A. van Oudenaarden
Validation of noise models for single-cell transcriptomics
Nature Methods 11, 705 – 714 (2014).
N. Ji, T. C. Middelkoop, R. A. Mentink, M. C. Betist, S. Tonegawa, D. Mooijman, H. C. Korswagen, and A. van Oudenaarden
Feedback control of gene expression variability in the Caenorhabditis elegans Wnt pathway
Cell 155, 869 – 880 (2013).
G. Neuert, B. Munsky, R. Z. Tan, L. Teytelman, M. Khammash, and A. van Oudenaarden
Systematic identification of signal-activated stochastic gene regulation
Science 339, 584 – 587 (2013).