September 2018 - New Publication
Our study reports the integrated experimental and computational pipeline to build a four-dimensional protein atlas of the dividing human cell, combining a resource of genome edited fluorescent knock-in cell lines, their characterization by absolutely quantitative live imaging and the integration and mining of this large and unprecedentedly rich data set by advanced bioimage informatics and machine learning. this novel approach is generic and scalable and can be employed to systematically map and mine dynamic protein localization networks that drive many cellular functions in dynamic cell atlas projects.
July 2018 - New Publication
We use light-sheet microscopy to show that two bipolar spindles form in the zygote and then independently congress the maternal and paternal genomes, keeping the parental genomes apart during the first cleavage. This provides a potential rationale for erroneous divisions into more than two blastomeric nuclei observed in mammalian zygotes and reveals the mechanism behind the observation that parental genomes occupy separate nuclear compartments in the two-cell embryo.
A Science perspective article written by Agata P. Zielinska and Melina Schuh, a Developmental Cell preview article by Arunika Das and Michael A. Lampson and a Current Biology dispatch by Adel Al Jord and Marie-Hélène Verlhac highlight the importance of Judith's work.
Also check out what's new on bioRxiv - Ellenberg Lab Preprints
In the link below from the iBioseminar website, watch Jan Ellenberg explaining how to perform high throughput content imaging screening with an update on the recent technologies developed in our lab and EMBL.
Our group is an international interdisciplinary team drawing its members from biology, physics, chemistry, computer science, and engineering. The overarching theme of the lab is to understand the molecular mechanism of the nuclear division cycle in a comprehensive manner in the physiological context of the intact living cell. To achieve this we develop and use a braod range of fluorescence-based imaging technologies to assay the functions of the involved molecular machinery non-invasively, automate imaging to address all its molecular components and computationally process image data to extract biochemical and biophysical parameters in order to generate mechanistic understanding and predictive models. Our biological questions are currently focused on three areas.