{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:56Z","timestamp":1772138096153,"version":"3.50.1"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2019,7,8]],"date-time":"2019-07-08T00:00:00Z","timestamp":1562544000000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"German Research Foundation","doi-asserted-by":"publisher","award":["BA2168\/16-1"],"award-info":[{"award-number":["BA2168\/16-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"German Research Foundation","doi-asserted-by":"publisher","award":["BA2168\/3-3"],"award-info":[{"award-number":["BA2168\/3-3"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Germany\u2019s Excellence Strategy","award":["390939984"],"award-info":[{"award-number":["390939984"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>SHAPE experiments are used to probe the structure of RNA molecules. We present ShaKer to predict SHAPE data for RNA using a graph-kernel-based machine learning approach that is trained on experimental SHAPE information. While other available methods require a manually curated reference structure, ShaKer predicts reactivity data based on sequence input only and by sampling the ensemble of possible structures. Thus, ShaKer is well placed to enable experiment-driven, transcriptome-wide SHAPE data prediction to enable the study of RNA structuredness and to improve RNA structure and RNA\u2013RNA interaction prediction. For performance evaluation, we use accuracy and accessibility comparing to experimental SHAPE data and competing methods. We can show that Shaker outperforms its competitors and is able to predict high quality SHAPE annotations even when no reference structure is provided.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>ShaKer is freely available at https:\/\/github.com\/BackofenLab\/ShaKer.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz395","type":"journal-article","created":{"date-parts":[[2019,6,25]],"date-time":"2019-06-25T10:52:47Z","timestamp":1561459967000},"page":"i354-i359","source":"Crossref","is-referenced-by-count":11,"title":["ShaKer: RNA SHAPE prediction using graph kernel"],"prefix":"10.1093","volume":"35","author":[{"given":"Stefan","family":"Mautner","sequence":"first","affiliation":[{"name":"Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany"}]},{"given":"Soheila","family":"Montaseri","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany"}]},{"given":"Milad","family":"Miladi","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany"}]},{"given":"Martin","family":"Raden","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany"}]},{"given":"Fabrizio","family":"Costa","sequence":"additional","affiliation":[{"name":"Department Computer Science, University of Exeter, Exeter, UK"}]},{"given":"Rolf","family":"Backofen","sequence":"additional","affiliation":[{"name":"Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany"},{"name":"Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany"}]}],"member":"286","published-online":{"date-parts":[[2019,7,5]]},"reference":[{"key":"2023062712335923300_btz395-B1","first-page":"D335","article-title":"Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families","volume":"46","author":"Bateman","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023062712335923300_btz395-B2","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1145\/2939672.2939785","volume-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Chen","year":"2016"},{"key":"2023062712335923300_btz395-B3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s40484-017-0093-6","article-title":"Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions","volume":"5","author":"Choudhary","year":"2017","journal-title":"Quant. 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