Author

Kotaro Kelley

New York Structural Biology Center

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1

Signature Assays, Organisms & Methods

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Assay:cryo-EM· 1 Approach:deep learning· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Assay:imaging· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Alex J. NobleiD· 1 shared Bonnie BergeriD· 1 shared Bridget CarragheriD· 1 shared Carl J. Negro· 1 shared Clinton S. PotteriD· 1 shared Edward T. EngiD· 1 shared Kelsey D. Jordan· 1 shared Mykhailo KopyloviD· 1 shared

Activity by Year

2018-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Alex J. NobleORCID

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2 papers

Recent·Most cited

Topaz-Denoise: general deep denoising models for cryoEM and cryoET

Tristan Bepler, Kotaro Kelley, Alex J. Noble, Bonnie Berger

Topaz-Denoise improves cryoEM and cryoET image quality by increasing SNR, enabling faster analysis and solving previously elusive structures.

Nature Communications · Oct 15, 2020Peer-reviewedBioinformatics

The impact of data reduction and lossy image formats on electron microscope images

Edward T. Eng, Mykhailo Kopylov, Carl J. Negro, Sarkis Dallaykan, William J. Rice, Kelsey D. Jordan, Kotaro Kelley, Bridget Carragher, Clinton S. Potter

This study examines how data compression and lossy image formats affect cryoEM reconstruction quality, finding that compressed data can still yield sub-2Å reconstructions.

bioRxiv · Oct 24, 2018 · PreprintBiophysics