Show simple item record

dc.contributor.authorGe, Ping
dc.contributor.authorIslam, Shahidul
dc.contributor.authorZhong, Cuncong
dc.contributor.authorZhang, Shaojie
dc.date.accessioned2019-11-15T18:09:55Z
dc.date.available2019-11-15T18:09:55Z
dc.date.issued2018-03-09
dc.identifier.citationPing Ge, Shahidul Islam, Cuncong Zhong, Shaojie Zhang, De novo discovery of structural motifs in RNA 3D structures through clustering, Nucleic Acids Research, Volume 46, Issue 9, 18 May 2018, Pages 4783–4793, https://doi.org/10.1093/nar/gky139en_US
dc.identifier.urihttp://hdl.handle.net/1808/29778
dc.description.abstractAs functional components in three-dimensional (3D) conformation of an RNA, the RNA structural motifs provide an easy way to associate the molecular architectures with their biological mechanisms. In the past years, many computational tools have been developed to search motif instances by using the existing knowledge of well-studied families. Recently, with the rapidly increasing number of resolved RNA 3D structures, there is an urgent need to discover novel motifs with the newly presented information. In this work, we classify all the loops in non-redundant RNA 3D structures to detect plausible RNA structural motif families by using a clustering pipeline. Compared with other clustering approaches, our method has two benefits: first, the underlying alignment algorithm is tolerant to the variations in 3D structures. Second, sophisticated downstream analysis has been performed to ensure the clusters are valid and easily applied to further research. The final clustering results contain many interesting new variants of known motif families, such as GNAA tetraloop, kink-turn, sarcin-ricin and T-loop. We have also discovered potential novel functional motifs conserved in ribosomal RNA, sgRNA, SRP RNA, riboswitch and ribozyme.en_US
dc.description.sponsorshipNational Institute of General Medical Sciences of the National Institutes of Health (NIH NIGMS) (R01GM102515)en_US
dc.description.sponsorshipFunding for open access charge: NIH NIGMS [R01 GM102515]en_US
dc.publisherOxford University Pressen_US
dc.rights© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. 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.comen_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/en_US
dc.titleDe novo discovery of structural motifs in RNA 3D structures through clusteringen_US
dc.typeArticleen_US
kusw.kuauthorZhong, Cuncong
kusw.kudepartmentElectrical Engineering and Computer Scienceen_US
dc.identifier.doi10.1093/nar/gky139en_US
dc.identifier.orcidhttp://orcid.org/0000-0002-4051-5549en_US
kusw.oaversionScholarly/refereed, author accepted manuscripten_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.
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) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. 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