Single-cell microscopy is a powerful tool that we use across all our biological questions. Ranging from microfluidics-based live-cell microscopy to follow cell growth and division over multiple cell cycles, quantification of mitochondrial network and DNA in live cells to single molecule FISH, microscopy can provide direct quantitative insights. Despite recent progress in AI-based approaches, image analysis can be very time-consuming and is often still the rate-limiting step. To address this, we use state-of-the-art deep-learning to improve automated image analysis and work on making these approaches easily accessible for a broad community. We envision that standardized tools and approaches will enable reproducibility and data sharing.

More information about Software developed in our lab can be found here.

Padovani, F., Čavka, I., Rodrigues Neves, A.R., Piñeiro López, C., Al-Refaie, N., Bolcato, L., Chatzitheodoridou, D., Chadha, Y., Su, X.A., Lengefeld, J., Cabianca, D.S., Köhler, S. & Schmoller, K.M. (2024) SpotMAX: a generalist framework for multi-dimensional automatic spot detection and quantification, bioRxiv

Vitacolonna, M., Bruch, R., Agaçi, A., Nürnberg, E., Cesetti, T., Keller, F., Padovani, F., Sauer, S., Schmoller, K.M., Reischl, M., Hafner, M. & Rudolf, R. (2024) A multiparametric analysis including single-cell and subcellular feature assessment reveals differential behavior of spheroid cultures on distinct ultra-low attachment plates types, Frontiers in Bioengineering and Biotechnology, 12, 1422235

Padovani, F., Mairhörmann, B., Falter-Braun, P., Lengefeld, J. & Schmoller, K.M. (2022) Segmentation, tracking and cell cycle analysis of live-cell imaging data with Cell-ACDC, BMC Biology, 20, 1-18

Cuny, A.P., Schlottmann, F.P., Ewald, J.C., Pelet, S. & Schmoller, K.M. (2022) Live cell microscopy: From image to insight, Biophysics Reviews, 3, 021302