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Abstractions are therefore needed to simplify downstream analyses, and thus make them computationally tractable. This can be achieved by various structure sampling algorithms. However, current sampling methods are still time consuming and frequently fail to represent key elements of the folding space.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>We introduce RNAxplorer, a novel adaptive sampling method to efficiently explore the structure space of RNAs. RNAxplorer uses dynamic programming to perform an efficient Boltzmann sampling in the presence of guiding potentials, which are accumulated into pseudo-energy terms and reflect similarity to already well-sampled structures. This way, we effectively steer sampling toward underrepresented or unexplored regions of the structure space.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We developed and applied different measures to benchmark our sampling methods against its competitors. Most of the measures show that RNAxplorer produces more diverse structure samples, yields rare conformations that may be inaccessible to other sampling methods and is better at finding the most relevant kinetic traps in the landscape. Thus, it produces a more representative coarse graining of the landscape, which is well suited to subsequently compute better approximations of RNA folding kinetics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availabilityand implementation<\/jats:title>\n                    <jats:p>https:\/\/github.com\/ViennaRNA\/RNAxplorer\/.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab066","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T18:59:51Z","timestamp":1612378791000},"page":"2126-2133","source":"Crossref","is-referenced-by-count":5,"title":["RNAxplorer: harnessing the power of guiding potentials to sample RNA landscapes"],"prefix":"10.1093","volume":"37","author":[{"given":"Gregor","family":"Entzian","sequence":"first","affiliation":[{"name":"Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna , Vienna 1090, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7132-0800","authenticated-orcid":false,"given":"Ivo L","family":"Hofacker","sequence":"additional","affiliation":[{"name":"Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna , Vienna 1090, Austria"},{"name":"Research Group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna , Vienna 1090, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7615-3930","authenticated-orcid":false,"given":"Yann","family":"Ponty","sequence":"additional","affiliation":[{"name":"LIX, CNRS UMR 7161, Ecole Polytechnique, Institut Polytechnique de Paris , Paris, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2144-698X","authenticated-orcid":false,"given":"Ronny","family":"Lorenz","sequence":"additional","affiliation":[{"name":"Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna , Vienna 1090, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2873-4236","authenticated-orcid":false,"given":"Andrea","family":"Tanzer","sequence":"additional","affiliation":[{"name":"Department of Theoretical Chemistry, Faculty of Chemistry, University of Vienna , Vienna 1090, Austria"},{"name":"Department of Cell and Developmental Biology, Center for Anatomy and Cell Biology, Medical University of Vienna , Vienna 1090, Austria"}]}],"member":"286","published-online":{"date-parts":[[2021,2,4]]},"reference":[{"key":"2023061310414841200_btab066-B1","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1063\/1.473299","article-title":"The topology of multidimensional potential energy surfaces: theory and application to peptide structure and kinetics","volume":"106","author":"Becker","year":"1997","journal-title":"J. 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