Full list of publications available on Google Scholar. Below is some recent, relevant work.

Nature Methods: Self-supervised deep learning encodes high-resolution features of protein subcellular localization Icon
July 25, 2022

In partnership with our colleagues from the Royer lab at the Biohub, we developed cytoself, an innovative deep-learning-based approach for fully self-supervised protein localization profiling and clustering.

bioRxiv: Self-Supervised Deep-Learning Encodes High-Resolution Features of Protein Subcellular Localization Icon
June 1, 2022

In partnership with our colleagues from the Royer lab at the Biohub, we developed cytoself, an innovative deep-learning-based approach for fully self-supervised protein localization profiling and clustering.

Science: OpenCell: Endogenous tagging for the cartography of human cellular organization Icon
March 11, 2022

This paper describes the first release of our flagship OpenCell dataset. We combined CRISPR, confocal live-cell imaging, mass spectrometry and machine learning to map the sub-cellular localization and interactions of 1,310 human proteins. We show that unsupervised clustering of our dataset facilitates biological discovery. Find the preprint here.

Journal of Cell Biology: WASP integrates substrate topology and cell polarity to guide neutrophil migration Icon
February 7, 2022

In this collaboration with the Weiner lab at UCSF, we used endogenous protein tagging to help uncover a role for the actin regulator WASP in the 3D migration of neutrophils.

Science: Pervasive functional translation of noncanonical human open reading frames Icon
March 6, 2020

In this collaboration with the Weissman lab at UCSF, we used our live imaging and proteomics pipeline to discover new functions for micro-peptides, very short proteins that are encoded all throughout the genome and whose function remains very mysterious.

nature methods: Epi-illumination SPIM for volumetric imaging with high spatial-temporal resolution Icon
June 1, 2019

In this collaboration with the Huang lab at UCSF, we leveraged a newly developed inverted light-sheet microscope for high-throughput 4D imaging of protein dynamics during cell division.