{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T23:30:21Z","timestamp":1783812621659,"version":"3.55.0"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2022,2,4]],"date-time":"2022-02-04T00:00:00Z","timestamp":1643932800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0504700"],"award-info":[{"award-number":["2017YFA0504700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFA0712401"],"award-info":[{"award-number":["2020YFA0712401"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFF0704300"],"award-info":[{"award-number":["2021YFF0704300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61932018"],"award-info":[{"award-number":["61932018"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072280"],"award-info":[{"award-number":["62072280"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072441"],"award-info":[{"award-number":["62072441"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31730023"],"award-info":[{"award-number":["31730023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31521002"],"award-info":[{"award-number":["31521002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002367","name":"Chinese Academy of Sciences","doi-asserted-by":"publisher","award":["XDB37010100"],"award-info":[{"award-number":["XDB37010100"]}],"id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Laboratory of Biomacromolecules of China","award":["2019KF07"],"award-info":[{"award-number":["2019KF07"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Cryo-electron microscopy (cryo-EM) is a widely used technology for ultrastructure determination, which constructs the 3D structures of protein and macromolecular complex from a set of 2D micrographs. However, limited by the electron beam dose, the micrographs in cryo-EM generally suffer from the extremely low signal-to-noise ratio (SNR), which hampers the efficiency and effectiveness of downstream analysis. Especially, the noise in cryo-EM is not simple additive or multiplicative noise whose statistical characteristics are quite different from the ones in natural image, extremely shackling the performance of conventional denoising methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we introduce the Noise-Transfer2Clean (NT2C), a denoising deep neural network (DNN) for cryo-EM to enhance image contrast and restore specimen signal, whose main idea is to improve the denoising performance by correctly learning the noise distribution of cryo-EM images and transferring the statistical nature of noise into the denoiser. Especially, to cope with the complex noise model in cryo-EM, we design a contrast-guided noise and signal re-weighted algorithm to achieve clean-noisy data synthesis and data augmentation, making our method authentically achieve signal restoration based on noise\u2019s true properties. Our work verifies the feasibility of denoising based on mining the complex cryo-EM noise patterns directly from the noise patches. Comprehensive experimental results on simulated datasets and real datasets show that NT2C achieved a notable improvement in image denoising, especially in background noise removal, compared with the commonly used methods. Moreover, a case study on the real dataset demonstrates that NT2C can greatly alleviate the obstacles caused by the SNR to particle picking and simplify the identifying of particles.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availabilityand implementation<\/jats:title>\n                    <jats:p>The code is available at https:\/\/github.com\/Lihongjia-ict\/NoiseTransfer2Clean\/.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac052","type":"journal-article","created":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T07:13:07Z","timestamp":1643353987000},"page":"2022-2029","source":"Crossref","is-referenced-by-count":31,"title":["Noise-Transfer2Clean: denoising cryo-EM images based on noise modeling and transfer"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7016-421X","authenticated-orcid":false,"given":"Hongjia","family":"Li","sequence":"first","affiliation":[{"name":"High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences , Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences , Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences , Beijing 100049, China"},{"name":"National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences , Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohua","family":"Wan","sequence":"additional","affiliation":[{"name":"High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences , Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhidong","family":"Yang","sequence":"additional","affiliation":[{"name":"High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences , Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences , Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengmin","family":"Li","sequence":"additional","affiliation":[{"name":"National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences , Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jintao","family":"Li","sequence":"additional","affiliation":[{"name":"High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences , Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renmin","family":"Han","sequence":"additional","affiliation":[{"name":"Research Center for Mathematics and Interdisciplinary Sciences, Shandong University , Qingdao 266237, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Zhu","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences , Beijing 100049, China"},{"name":"National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences , Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fa","family":"Zhang","sequence":"additional","affiliation":[{"name":"High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences , Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,2,4]]},"reference":[{"key":"2023020109010994600_btac052-B1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.tibs.2014.10.005","article-title":"How cryo-EM is revolutionizing structural biology","volume":"40","author":"Bai","year":"2015","journal-title":"Trends Biochem. Sci"},{"key":"2023020109010994600_btac052-B2","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.jsb.2009.02.012","article-title":"Determination of signal-to-noise ratios and spectral SNRs in cryo-EM low-dose imaging of molecules","volume":"166","author":"Baxter","year":"2009","journal-title":"J. Struct. Biol"},{"key":"2023020109010994600_btac052-B3","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/MSP.2019.2957822","article-title":"Single-particle cryo-electron microscopy: mathematical theory, computational challenges, and opportunities","volume":"37","author":"Bendory","year":"2020","journal-title":"IEEE Signal Process. Mag"},{"key":"2023020109010994600_btac052-B4","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1038\/s41592-019-0575-8","article-title":"Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs","volume":"16","author":"Bepler","year":"2019","journal-title":"Nat. Methods"},{"key":"2023020109010994600_btac052-B5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-18952-1","article-title":"Topaz-Denoise: general deep denoising models for cryo-EM and cryoET","volume":"11","author":"Bepler","year":"2020","journal-title":"Nat. Commun"},{"key":"2023020109010994600_btac052-B6","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1007\/978-1-4939-7000-1_26","article-title":"Protein Data Bank (PDB): the single global macromolecular structure archive","author":"Burley","year":"2017","journal-title":"Protein Crystallogr"},{"key":"2023020109010994600_btac052-B7","doi-asserted-by":"crossref","first-page":"e06380","DOI":"10.7554\/eLife.06380","article-title":"2.8 \u00c5 resolution reconstruction of the Thermoplasma acidophilum 20S proteasome using cryo-electron microscopy","volume":"4","author":"Campbell","year":"2015","journal-title":"Elife"},{"key":"2023020109010994600_btac052-B8","first-page":"3155","author":"Chen","year":"2018"},{"key":"2023020109010994600_btac052-B9","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1109\/34.1000236","article-title":"Mean shift: a robust approach toward feature space analysis","volume":"24","author":"Comaniciu","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"2023020109010994600_btac052-B10","doi-asserted-by":"crossref","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","article-title":"Image denoising by sparse 3-D transform-domain collaborative filtering","volume":"16","author":"Dabov","year":"2007","journal-title":"IEEE Trans. Image Process"},{"key":"2023020109010994600_btac052-B11","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1038\/nature20560","article-title":"The pathway to GTPase activation of elongation factor SelB on the ribosome","volume":"540","author":"Fischer","year":"2016","journal-title":"Nature"},{"key":"2023020109010994600_btac052-B12","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative adversarial networks","volume":"63","author":"Goodfellow","year":"2020","journal-title":"Commun. ACM"},{"key":"2023020109010994600_btac052-B13","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1109\/78.80892","article-title":"A class of fast Gaussian binomial filters for speech and image processing","volume":"39","author":"Haddad","year":"1991","journal-title":"IEEE Trans. Signal Process"},{"key":"2023020109010994600_btac052-B14","first-page":"448","author":"Ioffe","year":"2015"},{"key":"2023020109010994600_btac052-B15","first-page":"2129","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Long Beach, CA","author":"Krull","year":"2019"},{"key":"2023020109010994600_btac052-B16","first-page":"4681","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, Hawaii","author":"Ledig","year":"2017"},{"key":"2023020109010994600_btac052-B17","first-page":"2965","author":"Lehtinen","year":"2018"},{"key":"2023020109010994600_btac052-B18","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"Maas","year":"2013","journal-title":"Proc. ICML"},{"key":"2023020109010994600_btac052-B19","first-page":"2802","author":"Mao","year":"2016"},{"key":"2023020109010994600_btac052-B20","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/S0076-6879(10)82002-6","article-title":"Image restoration in cryo-electron microscopy","volume":"482","author":"Penczek","year":"2010","journal-title":"Methods Enzymol"},{"key":"2023020109010994600_btac052-B21","first-page":"234","volume-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention. Munich, Germany","author":"Ronneberger","year":"2015"},{"key":"2023020109010994600_btac052-B22","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.jsb.2011.06.010","article-title":"An adaptation of the Wiener filter suitable for analyzing images of isolated single particles","volume":"176","author":"Sindelar","year":"2011","journal-title":"J. Struct. Biol"},{"key":"2023020109010994600_btac052-B23","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.jsb.2013.05.008","article-title":"Image formation modeling in cryo-electron microscopy","volume":"183","author":"Vulovi\u0107","year":"2013","journal-title":"J. Struct. Biol"},{"key":"2023020109010994600_btac052-B24","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0304-3991(92)90011-8","article-title":"A brief look at imaging and contrast transfer","volume":"46","author":"Wade","year":"1992","journal-title":"Ultramicroscopy"},{"key":"2023020109010994600_btac052-B25","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process"},{"key":"2023020109010994600_btac052-B26","doi-asserted-by":"crossref","first-page":"e03080","DOI":"10.7554\/eLife.03080","article-title":"Cryo-EM structure of the Plasmodium falciparum 80S ribosome bound to the anti-protozoan drug emetine","volume":"3","author":"Wong","year":"2014","journal-title":"Elife"},{"key":"2023020109010994600_btac052-B27","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1109\/TCBB.2015.2415787","article-title":"A two-phase improved correlation method for automatic particle selection in Cryo-EM","volume":"14","author":"Zhang","year":"2017","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf"},{"key":"2023020109010994600_btac052-B28","first-page":"1","article-title":"PIXER: an automated particle-selection method based on segmentation using a deep neural network","volume":"20","author":"Zhang","year":"2019","journal-title":"BMC Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btac052\/42490383\/btac052.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/7\/2022\/49009421\/btac052.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/7\/2022\/49009421\/btac052.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T15:45:50Z","timestamp":1675266350000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/7\/2022\/6522116"}},"subtitle":[],"editor":[{"given":"Jinbo","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2022,2,4]]},"references-count":28,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2022,3,28]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac052","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.05.10.443396","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,4,1]]},"published":{"date-parts":[[2022,2,4]]}}}