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Emma Kaeller Lundberg - Associate Professor of Bioengineering and Pathology

Photo of smiling white female faculty member, Dr. Emma Lundberg, Associate Professor of Bioengineering and Medicine at Stanford University.
Bio-X Affiliated Faculty

Dr. Emma Lundberg's research is focused on spatial proteomics and cell biology. At the interface between bioimaging and proteomics are fundamental aspects of human cell biology systematically assessed at a single cell level using an antibody-based approach. The aim is to understand how human proteins are distributed in time and space, how variations and deviations in localization can contribute to cell type specificity as well as disease.

Compartmentalization of biological processes is a fundamental principle of eukaryotic cells that enables multiple processes to occur in parallel. The compartments are specialized for a particular cellular function and contain the molecules needed to fulfill it. Defects in compartment organization or protein mislocalization underlie the cause of many forms of human disease. Despite a great deal of research, basic questions about the spatial organization of many proteins and biological processes remain unanswered. Using computational image analysis, the Lundberg lab is also investigating variations of protein spatiotemporal expression patterns at the single cell level, in relation to the cell cycle or other deterministic factors.

A part of their work is the creation of the Cell Atlas, part of the Human Protein Atlas project, where the subcellular localization of all human proteins is being determined.

Through various measures the lab tries to engage a wider community in their work. For example through a Citizen Science project called “Project Discovery” for classification of protein patterns in microscope images, integrated into the massively multiplayer online Sci-Fi game Eve Online with over 300.000 participants, and through the Kaggle Challenges “Human Protein Atlas Image Classification Challenge”, and “Human Protein Atlas – Single Cell Classification Challenge”.