Cell Press Symposia: Next-generation cell biology: Advanced imaging, AI, and cellular engineering
In partnership with Tsinghua University and State Key Laboratory of Membrane Biology
May 19–21, 2027 | Beijing, China
Abstract submission deadline: January 8, 2027
We are entering a transformative era in cell biology, where rapid technological innovations and conceptual breakthroughs are reshaping the foundations of the field.
This Cell Press Symposium on next-generation cell biology highlights how interdisciplinary advances are driving paradigm shifts that expand our understanding of cellular organization and function.
Four areas in particular are poised to redefine the future of cell biology:
(1) advanced imaging technologies—from super-resolution approaches to next-generation electron microscopy— are enabling unprecedented visualization of intracellular physiology and architecture across space and time;
(2) insights into organelle crosstalk and metabolic organization are changing the understanding of cellular landscapes;
(3) artificial intelligence is revolutionizing data analysis and driving biological discovery at scale; and
(4) emerging quantitative and biophysical principles are reshaping cellular engineering efforts, including the building and reconstitution of cell-scale systems, toward groundbreaking discoveries and applications.
Together, these developments mark a new chapter for cell biology, one characterized by interdisciplinary collaboration and bold conceptual advances that promise to redefine the very nature of how we study and understand life at the cellular level.
Session 1: Mapping cellular physiology in space and time (imaging)
Goal: new imaging and measurement modalities that make intracellular physiology and architecture quantifiable across space and time, including 4D cellular physiology.
Session 2: Cellular landscapes: Organelle crosstalk and metabolic organization in space
Goal: Inter-organelle coupling and mesoscale organization, including membrane contact sites, organelle remodeling, condensate-linked compartmentalization, and spatial metabolic zoning.
Session 3: AI for cell biology
Goal: AI as a discovery engine for image-rich and spatial data, including segmentation, reconstruction, multimodal integration, and feature discovery at scale.
Session 4: Engineering cell biology
Goal: emerging quantitative and biophysical principles are reshaping cellular engineering, including the building and reconstitution of cell-scale systems, toward groundbreaking discoveries and applications.
Organizers
-
Li Yu, Tsinghua University, China
-
Alba-Diz Munoz, European Molecular Biology Laboratory, Germany
-
Shawnna Buttery, Editor-in-chief, Cell Reports, Cell Press
-
Ilaria Carnevale, Lead editor, Trends Open, Cell Press
-
Luis Gomes, Senior scientific editor, Cell, Cell Press
Organizing committee
-
Liang Ge, Tsinghua University, China
-
Qiangfeng Cliff Zhang, Tsinghua University, China
-
Shuguang Li, Tsinghua University, China

