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dc.contributor.authorLi, Haoyang
dc.contributor.authorTian, Shuye
dc.contributor.authorLi, Yu
dc.contributor.authorFang, Qiming
dc.contributor.authorTan, Renbo
dc.contributor.authorPan, Yijie
dc.contributor.authorHuang, Chao
dc.contributor.authorXu, Ying
dc.contributor.authorGao, Xin
dc.date.accessioned2020-06-25T12:48:01Z
dc.date.available2020-06-25T12:48:01Z
dc.date.issued2020-06-23
dc.date.submitted2019-10-14
dc.identifier.citationLi, H., Tian, S., Li, Y., Fang, Q., Tan, R., Pan, Y., … Gao, X. (2020). Modern Deep Learning in Bioinformatics. Journal of Molecular Cell Biology. doi:10.1093/jmcb/mjaa030
dc.identifier.issn1674-2788
dc.identifier.pmid32573721
dc.identifier.doi10.1093/jmcb/mjaa030
dc.identifier.urihttp://hdl.handle.net/10754/663856
dc.description.abstractDeep learning (DL) has shown explosive growth in its application to bioinformatics and has demonstrated thrillingly promising power to mine the complex relationship hidden in large-scale biological and biomedical data. A number of comprehensive reviews have been published on such applications, ranging from high-level reviews with future perspectives to those mainly serving as tutorials. These reviews have provided an excellent introduction to and guideline for applications of DL in bioinformatics, covering multiple types of machine learning (ML) problems, different DL architectures, and ranges of biological/biomedical problems. However, most of these reviews have focused on previous research, whereas current trends in the principled DL field and perspectives on their future developments and potential new applications to biology and biomedicine are still scarce. We will focus on modern DL, the ongoing trends and future directions of the principled DL field, and postulate new and major applications in bioinformatics.
dc.publisherOxford University Press (OUP)
dc.relation.urlhttps://academic.oup.com/jmcb/advance-article/doi/10.1093/jmcb/mjaa030/5861537
dc.rights© The Author(s) 2020. Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.titleModern Deep Learning in Bioinformatics.
dc.typeArticle
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStructural and Functional Bioinformatics Group
dc.identifier.journalJournal of molecular cell biology
dc.eprint.versionPost-print
dc.contributor.institutionCancer Systems Biology Center, the China-Japan Union Hospital, Jilin University, Changchun 130033, China
dc.contributor.institutionMOE Key Laboratory of Symbolic Computation and Knowledge Engineering, College of Computer Science and Technology, Jilin University, Changchun 130012, China
dc.contributor.institutionDepartment of Biology, Southern University of Science and Technology, Shenzhen 518055, China
dc.contributor.institutionSchool of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
dc.contributor.institutionNingbo Institute of Information Technology Application, Chinese Academy of Sciences, Ningbo, China
dc.contributor.institutionComputational Systems Biology Lab, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
kaust.personLi, Yu
kaust.personGao, Xin
dc.date.accepted2020-04-23
refterms.dateFOA2020-06-25T12:50:39Z


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© The Author(s) 2020. Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
Except where otherwise noted, this item's license is described as © The Author(s) 2020. Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com