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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.
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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  Data: Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data.
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  Data: <searchLink fieldCode="AU" term="%22Ziatdinov+M%22">Ziatdinov M</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Zhang+S%22">Zhang S</searchLink>; Materials Science and Engineering, University of Washington, Seattle, Washington 98195, United States.; Physical Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.<br /><searchLink fieldCode="AU" term="%22Dollar+O%22">Dollar O</searchLink>; Chemical Engineering, University of Washington, Seattle, Washington 98195, United States.<br /><searchLink fieldCode="AU" term="%22Pfaendtner+J%22">Pfaendtner J</searchLink>; Chemical Engineering, University of Washington, Seattle, Washington 98195, United States.<br /><searchLink fieldCode="AU" term="%22Mundy+CJ%22">Mundy CJ</searchLink>; Physical Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.; Chemical Engineering, University of Washington, Seattle, Washington 98195, United States.<br /><searchLink fieldCode="AU" term="%22Li+X%22">Li X</searchLink>; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.<br /><searchLink fieldCode="AU" term="%22Pyles+H%22">Pyles H</searchLink>; Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States.; Institute for Protein Design, University of Washington, Seattle, Washington 98195, United States.<br /><searchLink fieldCode="AU" term="%22Baker+D%22">Baker D</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22De+Yoreo+JJ%22">De Yoreo JJ</searchLink>; Materials Science and Engineering, University of Washington, Seattle, Washington 98195, United States.; Physical Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.<br /><searchLink fieldCode="AU" term="%22Kalinin+SV%22">Kalinin SV</searchLink>; Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.
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  Data: <searchLink fieldCode="JN" term="%22101088070%22">Nano letters</searchLink> [Nano Lett] 2021 Jan 13; Vol. 21 (1), pp. 158-165. <i>Date of Electronic Publication: </i>2020 Dec 11.
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  Data: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, Non-U.S. Gov't
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22American+Chemical+Society%22">American Chemical Society </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101088070 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1530-6992 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2215306984%22">15306984 </searchLink><i>NLM ISO Abbreviation: </i>Nano Lett <i>Subsets: </i>MEDLINE; PubMed not MEDLINE
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