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    Correction: DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction (BMC Bioinformatics, (2020), 21, S3, (63), 10.1186/s12859-020-3342-z)

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    Date
    2022-08-22
    Author
    Thapa, Niraj
    Chaudhari, Meenal
    McManus, Sean
    Roy, Kaushik
    Newman, Robert H.
    Hiroto, Saigo
    KC, Dukka B.
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    Citation
    Thapa, N., Chaudhari, M., McManus, S. et al. Correction: DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction. BMC Bioinformatics 23, 349 (2022). https://doi.org/10.1186/s12859-022-04844-2
    Abstract
    After publication of this supplement article [1], it is requested to correct the below errors in the article: On page 1, the Result of Abstract should be changed to: Results: Using an independent test set of experimentally identified succinylation sites, our method achieved efficiency scores of 79%, 68.7% and 0.27 for sensitivity, specificity and MCC respectively, with an area under the receiver operator characteristic (ROC) curve of 0.8. In side-by-side comparisons with previously described succinylation site predictors, DeepSuccinylSite produces similar or better results compared to the other state-of-the-art predictors. On page 7, Last paragraph on right should be changed from Consequently, DeepSuccinylSite achieved a significantly higher performance as measured by MCC. Indeed, DeepSuccinylSite exhibited an ~ 62% increase in MCC when compared to the next highest method, GPSuc. to: Consequently, DeepSuccinylSite achieved an MCC score (at decision boundary of 0.5) on par with the top performingmethod, GPSuc. On page 2, in Table 1, the negative data of Independent Test should be 2977 rather than 254. On page 8, in Table 6, the MCC data of DeepSuccinylSite should be 0.27 rather than 0.48.
    Description
    Click on the DOI to access this article (may not be free). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
    URI
    https://doi.org/10.1186/s12859-022-04844-2
    https://soar.wichita.edu/handle/10057/23906
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