We investigate the molecular details that determine how, where and when motor proteins transport intracellular cargo to better understand their role in human health and disease.

Structural Cell Biology

We are a research team that is trying to understand the molecular details that determine how, where, and when motor proteins transport intracellular cargo. The past thirty years of cell biology research have set the stage for us to determine the general principles that underlie the complex process of intracellular transport. 

Overaching questions that we are trying to answer (and that keep us up at night):

  • How is specificity determined between motor proteins and cargo?
  • How are the activities of multi-motor complexes regulated? 
  • What are the molecular consequences of neurodegenerative disease-causing mutations? 

We are approaching these questions from a number of different angles, using cryo-electron microscopy, single molecule TIRF, and biochemistry to relate protein structure to its activity in a cell. 

Tool Development for Cryo-Electron Microscopy

As a fast-growing part of structural biology, cryo-electron microscopy (cryo-EM) is determining new and exciting macromolecular structures on a seemingly daily basis. Despite its power, cryo-EM is a field that needs to undergo rapid maturation to allow for new users to come into the fold to solve structures. 

Our laboratory is designing new algorithms and building computational infrastructure to implement streamlined, intelligent cryo-EM workflows.

Cryo-EM data collection remains bespoke, cumbersome and inefficient. We are leveraging databases of 350,000+ micrographs in the laboratory to determine optimal path planning across cryo-EM grids. Navigating on a cryo-EM grid is akin exploring an unknown landscape without any prior knowledge of ‘good’ and ‘bad’ areas. We believe that the incorporation of artificial intelligence will enable high-quality, automated cryo-EM data collection to remove human users from microscope operation.

Beyond data collection, we are constructing data processing pipelines that capture human expertise into trained neural networks. We believe that early steps in cryo-EM need to become automated and robust so that automation in data collection will be coupled to higher throughput processing.


Unlike other structural biology tools, cryo-EM necessarily requires access to high-performance computing capabilities. The large computational workload will limit the throughput and spread of cryo-EM due to users 1) waiting for cluster time or 2) being unable to find a cluster amenable for cryo-EM.

To address these problems, we have built cloud computing resources at Amazon Web Services and the San Diego Supercomputer Center to help give users access to cryo-EM so they can focus on understanding biology instead of dealing with Linux.

Cryo-EM in the Cloud

The 'cloud' has become an integral part of big data processing across many disciplines. Due to the ever-increasing computational demand of cryo-EM, turning to cloud resources can allow for many users to solve structures as-fast-as-possible without any queueing / wait times.

This website will serve as the central location that will document and update cloud-computing resources available to the cryo-EM community.


The COSMIC² science gateway is a public resource for determining cryo-EM structures and predicting protein structures using AlphaFold. COSMIC2 provides a simple web interface to access National Science Foundation XSEDE supercomputing resources.