CryoTransformer: a transformer model for picking protein particles from Cryo-EM micrographs

Dhakal, Ashwin; Gyawali, Rajan; Wang, Liguo; Cheng, Jianlin

doi:10.1093/bioinformatics/btae109

Title: CryoTransformer: a transformer model for picking protein particles from Cryo-EM micrographs

Journal Article · 24 February 2024 · Bioinformatics

DOI: https://doi.org/10.1093/bioinformatics/btae109 · OSTI ID:2318525

Dhakal, Ashwin ^[1]; Gyawali, Rajan ^[1]; Wang, Liguo ^[2]; Cheng, Jianlin ^[1]

University of Missouri, Columbia, MO (United States)
Brookhaven National Laboratory (BNL), Upton, NY (United States)

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of large protein complexes. Picking single protein particles from cryo-EM micrographs (images) is a crucial step in reconstructing protein structures from them. However, the widely used template-based particle picking process requires some manual particle picking and is labor-intensive and time-consuming. Though machine learning and artificial intelligence (AI) can potentially automate particle picking, the current AI methods pick particles with low precision or low recall. The erroneously picked particles can severely reduce the quality of reconstructed protein structures, especially for the micrographs with low signal-to-noise-ratio (SNR).

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Research Organization:: Donald Danforth Plant Science Center, St. Louis, MO (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0020400

OSTI ID:: 2318525

Journal Information:: Bioinformatics, Vol. 40, Issue 3; ISSN 1367-4811

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

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