Author Correction: Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways

Author Correction: Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways www.nature.com/scientificreports OPEN Author Correction: Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways 1,3 1 3 1,4 1 5 Renchu Guan , Xu Wang , Mary Qu Yang , Yu Zhang , Fengfeng Zhou , Chen Yang & 1,2 Published: xx xx xxxx Yanchun Liang Correction to: Scientific Reports https://doi.org/10.1038/s41598-017-17842-9, published online 10 January 2018 e A Th cknowledgements section of this Article is incomplete. “The authors are grateful for the support of the National Natural Science Foundation of China (No.61572228, No.61472158, No.61300147, No.61602207), United States National Institutes of Health (NIH) Academic Research Enhancement Award (No.1R15GM114739), National Institute of General Medical Sciences (NIH/NIGMS) (No.5P20GM103429), United States Food and Drug Administration (FDA) (No.HHSF223201510172C), the Science Technology Development Project from Jilin Province (No.20160101247JC), Zhuhai Premier-Discipline Enhancement Scheme and Guangdong Premier Key-Discipline Enhancement Scheme. This work was partially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13040400) and a start-up grant from the Jilin University. We thank KEGG group for supporting pathway data.” should read: “The authors are grateful for the support of the National Natural Science Foundation of China (No.61572228, No.61472158, No.61300147, No.61602207), United States National Institutes of Health (NIH) Academic Research Enhancement Award (No.1R15GM114739), National Institute of General Medical Sciences (NIH/NIGMS) (No.5P20GM103429), the Science Technology Development Project from Jilin Province (No.20160101247JC), Zhuhai Premier-Discipline Enhancement Scheme and Guangdong Premier Key-Discipline Enhancement Scheme. This work was partially supported by the United States Food and Drug Administration (FDA), contract No. HHSF223201510172C and HHSF223201610111C. However, the information contained herein represents the position of the author(s) and not necessarily that of the NIH and FDA. This work was partially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13040400) and a start-up grant from the Jilin University. We thank KEGG group for supporting pathway data.” Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry, College of Computer Science and Technology, Jilin University, Changchun, 130012, China. Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Zhuhai College of Jilin University, Zhuhai, 519041, China. MidSouth Bioinformatics Center and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and Univ. of Arkansas Medical Sciences, Little Rock, AR, 72204, USA. Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, University of Chinese Academy of Sciences, Beijing, 100093, China. College of Earth Sciences, Jilin University, Changchun, 130061, China. Renchu Guan and Xu Wang contributed equally to this work. Correspondence and requests for materials should be addressed to C.Y. (email: yangc616@jlu.edu.cn) or Y.L. (email: ycliang@jlu.edu.cn) SCIENtIfIC REPO R ts | (2018) 8:8995 | DOI:10.1038/s41598-018-27349-6 1 www.nature.com/scientificreports/ Open Access 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 Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted 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 license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2018 SCIENtIfIC REPO R ts | (2018) 8:8995 | DOI:10.1038/s41598-018-27349-6 2 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Scientific Reports Springer Journals

Author Correction: Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways

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Nature Publishing Group UK
Copyright
Copyright © 2018 by The Author(s)
Subject
Science, Humanities and Social Sciences, multidisciplinary; Science, Humanities and Social Sciences, multidisciplinary; Science, multidisciplinary
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2045-2322
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10.1038/s41598-018-27349-6
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Abstract

www.nature.com/scientificreports OPEN Author Correction: Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways 1,3 1 3 1,4 1 5 Renchu Guan , Xu Wang , Mary Qu Yang , Yu Zhang , Fengfeng Zhou , Chen Yang & 1,2 Published: xx xx xxxx Yanchun Liang Correction to: Scientific Reports https://doi.org/10.1038/s41598-017-17842-9, published online 10 January 2018 e A Th cknowledgements section of this Article is incomplete. “The authors are grateful for the support of the National Natural Science Foundation of China (No.61572228, No.61472158, No.61300147, No.61602207), United States National Institutes of Health (NIH) Academic Research Enhancement Award (No.1R15GM114739), National Institute of General Medical Sciences (NIH/NIGMS) (No.5P20GM103429), United States Food and Drug Administration (FDA) (No.HHSF223201510172C), the Science Technology Development Project from Jilin Province (No.20160101247JC), Zhuhai Premier-Discipline Enhancement Scheme and Guangdong Premier Key-Discipline Enhancement Scheme. This work was partially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13040400) and a start-up grant from the Jilin University. We thank KEGG group for supporting pathway data.” should read: “The authors are grateful for the support of the National Natural Science Foundation of China (No.61572228, No.61472158, No.61300147, No.61602207), United States National Institutes of Health (NIH) Academic Research Enhancement Award (No.1R15GM114739), National Institute of General Medical Sciences (NIH/NIGMS) (No.5P20GM103429), the Science Technology Development Project from Jilin Province (No.20160101247JC), Zhuhai Premier-Discipline Enhancement Scheme and Guangdong Premier Key-Discipline Enhancement Scheme. This work was partially supported by the United States Food and Drug Administration (FDA), contract No. HHSF223201510172C and HHSF223201610111C. However, the information contained herein represents the position of the author(s) and not necessarily that of the NIH and FDA. This work was partially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13040400) and a start-up grant from the Jilin University. We thank KEGG group for supporting pathway data.” Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry, College of Computer Science and Technology, Jilin University, Changchun, 130012, China. Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Zhuhai College of Jilin University, Zhuhai, 519041, China. MidSouth Bioinformatics Center and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and Univ. of Arkansas Medical Sciences, Little Rock, AR, 72204, USA. Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, University of Chinese Academy of Sciences, Beijing, 100093, China. College of Earth Sciences, Jilin University, Changchun, 130061, China. Renchu Guan and Xu Wang contributed equally to this work. Correspondence and requests for materials should be addressed to C.Y. (email: yangc616@jlu.edu.cn) or Y.L. (email: ycliang@jlu.edu.cn) SCIENtIfIC REPO R ts | (2018) 8:8995 | DOI:10.1038/s41598-018-27349-6 1 www.nature.com/scientificreports/ Open Access 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 Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted 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 license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2018 SCIENtIfIC REPO R ts | (2018) 8:8995 | DOI:10.1038/s41598-018-27349-6 2

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Scientific ReportsSpringer Journals

Published: Jun 7, 2018

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