In the Department of Data Science we generate knowledge from data to advance neuroscience and ophthalmology.
01
Cadwell, C. R., Scala, F., Fahey, P. G., Kobak, D., Mulherkar, S., Sinz, F. H., ... & Tolias, A. S.
Cell type composition and circuit organization of clonally related excitatory neurons in the juvenile mouse neocortex.
02
Berens, P., Waldstein, S. M., Ayhan, M. S., Kuemmerle, L., Agostini, H., Stahl, A., & Ziemssen, F.
Potential of methods of artificial intelligence for quality assurance.
03
Grote, T., & Berens, P.
On the ethics of algorithmic decision-making in healthcare.
04
Schröder, C., James, B., Lagnado, L., & Berens, P.
Approximate bayesian inference for a mechanistic model of vesicle release at a ribbon synapse.
05
Kobak, D., & Berens, P.
The art of using t-SNE for single-cell transcriptomics.
06
Kobak, D., Linderman, G., Steinerberger, S., Kluger, Y., & Berens, P.
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations.
07
Scala, F., Kobak, D., Shan, S., Bernaerts, Y., Laturnus, S., Cadwell, C. R., ... Berens, P., ... & Tolias, A. S
Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas
08
Rogerson, L. E., Zhao, Z., Franke, K., Euler, T., & Berens, P.
Bayesian hypothesis testing and experimental design for two-photon imaging data.
09
Rosón, M. R., Bauer, Y., Kotkat, A. H., Berens, P., Euler, T., & Busse, L.
Mouse dLGN receives functional input from a diverse population of retinal ganglion cells with limited convergence.
10
Berens, P., & Ayhan, M. S.
Proprietary data formats block health research.
11
Dhande, O. S., Stafford, B. K., Franke, K., El-Danaf, R., Percival, K. A., Phan, A. H., ..., Berens, P., ... & Huberman, A. D