Alberto Bartesaghi

About

Alberto Bartesaghi, PhD, is an Associate Professor of Computer Science and Biochemistry at Duke University, a position he has held since 2018. He earned his PhD in Electrical and Computer Engineering from the University of Minnesota in 2005. Following his doctoral studies, he served as an Associate Scientist at the National Cancer Institute at the National Institutes of Health in Bethesda, MD from 2005 to 2018. His research lab focuses on developing computational methods to solve the structure of large macromolecular complexes using advanced imaging techniques such as single particle cryo-electron microscopy, cryo-electron tomography, and sub-volume averaging. Beyond structural biology, his interests extend to machine learning, computer vision, image processing, and high-performance computing, reflecting a broad expertise in computational approaches to biological and biomedical challenges.

Research topics

• Biology
• Artificial Intelligence
• Computational biology
• Virology
• Computer Science
• Computer vision
• Physics
• Mathematics
• Optics
• Molecular biology

Selected publications

• Structural basis of NPR1 in activating plant immunity

  Nature · 2022 · 193 citations

  PublisherOA PDFDOI

• Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography

  Nature Communications · 2021 · 99 citations

  Senior authorCorresponding

  Tomographic reconstruction of cryopreserved specimens imaged in an electron microscope followed by extraction and averaging of sub-volumes has been successfully used to derive atomic models of macromolecules in their biological environment. Eliminating biochemical isolation steps required by other techniques, this method opens up the cell to in-situ structural studies. However, the need to compensate for errors in targeting introduced during mechanical navigation of the specimen significantly sl…

  DOI

• Fab-dimerized glycan-reactive antibodies are a structural category of natural antibodies

  Cell · 2021 · 90 citations

  DOI

• nextPYP: a comprehensive and scalable platform for characterizing protein variability in situ using single-particle cryo-electron tomography

  Nature Methods · 2023-10-26 · 51 citations

  articleOpen accessSenior author

  Single-particle cryo-electron tomography is an emerging technique capable of determining the structure of proteins imaged within the native context of cells at molecular resolution. While high-throughput techniques for sample preparation and tilt-series acquisition are beginning to provide sufficient data to allow structural studies of proteins at physiological concentrations, the complex data analysis pipeline and the demanding storage and computational requirements pose major barriers for the…

  PublisherOA PDFDOI

• Structural Basis for Virulence Activation of Francisella tularensis

  Molecular Cell · 2020 · 36 citations

  PublisherOA PDFDOI

Frequent coauthors

• Sriram Subramaniam

  201 shared

• Mario J. Borgnia

  National Institutes of Health

  162 shared

• Alan Merk

  Frederick National Laboratory for Cancer Research

  68 shared

• Jacqueline L.S. Milne

  National Cancer Institute

  67 shared

• Doreen Matthies

  50 shared

• Prashant Rao

  Beth Israel Deaconess Medical Center

  50 shared

• Joel R. Meyerson

  Weill Cornell Medicine

  42 shared

• Soojay Banerjee

  National Cancer Institute

  40 shared

Labs

• Bartesaghi LabPI

Similar researchers at Duke University

• John H. Reifh-68
• Pankaj K. Agarwalh-62
• Cynthia D. Rudinh-56