Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data.
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| Title: | Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data. |
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| Authors: | Ziatdinov M; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.; Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States., Zhang S; Materials Science and Engineering, University of Washington, Seattle, Washington 98195, United States.; Physical Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Dollar O; Chemical Engineering, University of Washington, Seattle, Washington 98195, United States., Pfaendtner J; Chemical Engineering, University of Washington, Seattle, Washington 98195, United States., Mundy CJ; Physical Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.; Chemical Engineering, University of Washington, Seattle, Washington 98195, United States., Li X; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States., Pyles H; Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States.; Institute for Protein Design, University of Washington, Seattle, Washington 98195, United States., Baker D; Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States.; Institute for Protein Design, University of Washington, Seattle, Washington 98195, United States.; Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, United States., De Yoreo JJ; Materials Science and Engineering, University of Washington, Seattle, Washington 98195, United States.; Physical Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Kalinin SV; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States. |
| Source: | Nano letters [Nano Lett] 2021 Jan 13; Vol. 21 (1), pp. 158-165. Date of Electronic Publication: 2020 Dec 11. |
| Publication Type: | Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: American Chemical Society Country of Publication: United States NLM ID: 101088070 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1530-6992 (Electronic) Linking ISSN: 15306984 NLM ISO Abbreviation: Nano Lett Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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