{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T08:57:02Z","timestamp":1775379422811,"version":"3.50.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T00:00:00Z","timestamp":1604275200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EvryRNA"},{"DOI":"10.13039\/501100007149","name":"Genopole","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007149","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Applied research in machine learning progresses faster when a clean dataset is available and ready to use. Several datasets have been proposed and released over the years for specific tasks such as image classification, speech-recognition and more recently for protein structure prediction. However, for the fundamental problem of RNA structure prediction, information is spread between several databases depending on the level we are interested in: sequence, secondary structure, 3D structure or interactions with other macromolecules. In order to speed-up advances in machine-learning based approaches for RNA secondary and\/or 3D structure prediction, a dataset integrating all this information is required, to avoid spending time on data gathering and cleaning.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Here, we propose the first attempt of a standardized and automatically generated dataset dedicated to RNA combining together: RNA sequences, homology information (under the form of position-specific scoring matrices) and information derived by annotation of available 3D structures (including secondary structure, canonical and non-canonical interactions and backbone torsion angles). The data are retrieved from public databases PDB, Rfam and SILVA. The paper describes the procedure to build such dataset and the RNA structure descriptors we provide. Some statistical descriptions of the resulting dataset are also provided.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The dataset is updated every month and available online (in flat-text file format) on the EvryRNA software platform (https:\/\/evryrna.ibisc.univ-evry.fr\/evryrna\/rnanet). An efficient parallel pipeline to build the dataset is also provided for easy reproduction or modification.<\/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\/btaa944","type":"journal-article","created":{"date-parts":[[2020,10,27]],"date-time":"2020-10-27T12:49:08Z","timestamp":1603802948000},"page":"1218-1224","source":"Crossref","is-referenced-by-count":10,"title":["RNANet: an automatically built dual-source dataset integrating homologous sequences and RNA structures"],"prefix":"10.1093","volume":"37","author":[{"given":"Louis","family":"Becquey","sequence":"first","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, Univ Evry, IBISC , Evry-Courcouronnes 91020, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Angel","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, Univ Evry, IBISC , Evry-Courcouronnes 91020, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fariza","family":"Tahi","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, Univ Evry, IBISC , Evry-Courcouronnes 91020, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,12,7]]},"reference":[{"key":"2023051706062087000_btaa944-B1","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.cels.2019.03.006","article-title":"End-to-end differentiable learning of protein structure","volume":"8","author":"AlQuraishi","year":"2019","journal-title":"Cell Syst"},{"key":"2023051706062087000_btaa944-B2","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1186\/s12859-019-2932-0","article-title":"ProteinNet: a standardized data set for machine learning of protein structure","volume":"20","author":"AlQuraishi","year":"2019","journal-title":"BMC Bioinformatics"},{"key":"2023051706062087000_btaa944-B3","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1093\/bioinformatics\/btp163","article-title":"Biopython: freely available python tools for computational molecular biology and bioinformatics","volume":"25","author":"Cock","year":"2009","journal-title":"Bioinformatics"},{"key":"2023051706062087000_btaa944-B4","doi-asserted-by":"crossref","first-page":"e90","DOI":"10.1093\/bioinformatics\/btl246","article-title":"CONTRAfold: RNA secondary structure prediction without physics-based models","volume":"22","author":"Do","year":"2006","journal-title":"Bioinformatics"},{"key":"2023051706062087000_btaa944-B5","doi-asserted-by":"crossref","first-page":"1465","DOI":"10.1006\/jmbi.1998.2233","article-title":"Stepping through an RNA structure: a novel approach to conformational analysis","volume":"284","author":"Duarte","year":"1998","journal-title":"J. Mol. Biol"},{"key":"2023051706062087000_btaa944-B6","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1186\/1471-2105-11-431","article-title":"Hidden Markov model speed heuristic and iterative HMM search procedure","volume":"11","author":"Johnson","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023051706062087000_btaa944-B7","doi-asserted-by":"crossref","first-page":"D335","DOI":"10.1093\/nar\/gkx1038","article-title":"Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families","volume":"46","author":"Kalvari","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2023051706062087000_btaa944-B8","doi-asserted-by":"crossref","first-page":"8177","DOI":"10.1073\/pnas.0911888107","article-title":"Semiautomated model building for RNA crystallography using a directed rotameric approach","volume":"107","author":"Keating","year":"2010","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023051706062087000_btaa944-B9","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1017\/S0033583511000059","article-title":"A new way to see RNA","volume":"44","author":"Keating","year":"2011","journal-title":"Q. Rev. Biophys"},{"key":"2023051706062087000_btaa944-B10","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1017\/S1355838201002515","article-title":"Geometric nomenclature and classification of RNA base pairs","volume":"7","author":"Leontis","year":"2001","journal-title":"RNA"},{"key":"2023051706062087000_btaa944-B11","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/978-3-642-25740-7_13","volume-title":"RNA 3D Structure Analysis and Prediction","author":"Leontis","year":"2012"},{"key":"2023051706062087000_btaa944-B12","first-page":"e142","article-title":"DSSR: an integrated software tool for dissecting the spatial structure of RNA","volume":"43","author":"Lu","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2023051706062087000_btaa944-B13","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1186\/s12859-019-3120-y","article-title":"RNA 3D structure prediction guided by independent folding of homologous sequences","volume":"20","author":"Magnus","year":"2019","journal-title":"BMC Bioinformatics"},{"key":"2023051706062087000_btaa944-B14","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1146\/annurev-biophys-070816-034125","article-title":"RNA structure: advances and assessment of 3D structure prediction","volume":"46","author":"Miao","year":"2017","journal-title":"Annu. Rev. Biophys"},{"key":"2023051706062087000_btaa944-B15","doi-asserted-by":"crossref","first-page":"2933","DOI":"10.1093\/bioinformatics\/btt509","article-title":"Infernal 1.1: 100-fold faster RNA homology searches","volume":"29","author":"Nawrocki","year":"2013","journal-title":"Bioinformatics"},{"key":"2023051706062087000_btaa944-B16","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1261\/rna.039438.113","article-title":"Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas","volume":"19","author":"Petrov","year":"2013","journal-title":"RNA"},{"key":"2023051706062087000_btaa944-B17","doi-asserted-by":"crossref","first-page":"7188","DOI":"10.1093\/nar\/gkm864","article-title":"SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB","volume":"35","author":"Pruesse","year":"2007","journal-title":"Nucleic Acids Res"},{"key":"2023051706062087000_btaa944-B18","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.1093\/bioinformatics\/bts252","article-title":"SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes","volume":"28","author":"Pruesse","year":"2012","journal-title":"Bioinformatics"},{"key":"2023051706062087000_btaa944-B19","doi-asserted-by":"crossref","first-page":"3841","DOI":"10.1093\/nar\/gky197","article-title":"Mining for recurrent long-range interactions in RNA structures reveals embedded hierarchies in network families","volume":"46","author":"Reinharz","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2023051706062087000_btaa944-B20","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1038\/nmeth.1818","article-title":"HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment","volume":"9","author":"Remmert","year":"2012","journal-title":"Nat. Methods"},{"key":"2023051706062087000_btaa944-B21","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1007\/s00285-007-0110-x","article-title":"FR3D: finding local and composite recurrent structural motifs in RNA 3D structures","volume":"56","author":"Sarver","year":"2007","journal-title":"J. Math. Biol"},{"key":"2023051706062087000_btaa944-B22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-019-13395-9","article-title":"RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning","volume":"10","author":"Singh","year":"2019","journal-title":"Nat. Commun"},{"key":"2023051706062087000_btaa944-B23","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1038\/nbt.3988","article-title":"MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets","volume":"35","author":"Steinegger","year":"2017","journal-title":"Nat. Biotechnol"},{"key":"2023051706062087000_btaa944-B24","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1016\/j.jmb.2007.06.058","article-title":"Evaluating and learning from RNA pseudotorsional space: quantitative validation of a reduced representation for RNA structure","volume":"372","author":"Wadley","year":"2007","journal-title":"J. Mol. Biol"},{"key":"2023051706062087000_btaa944-B25","doi-asserted-by":"crossref","first-page":"16856","DOI":"10.1073\/pnas.1821309116","article-title":"Distance-based protein folding powered by deep learning","volume":"116","author":"Xu","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa944\/34752890\/btaa944.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/9\/1218\/50359645\/btaa944.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/9\/1218\/50359645\/btaa944.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T06:13:03Z","timestamp":1684303983000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/37\/9\/1218\/5948998"}},"subtitle":[],"editor":[{"given":"Martelli","family":"Pier Luigi","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2020,12,7]]},"references-count":25,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2021,6,9]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa944","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2021,5,1]]},"published":{"date-parts":[[2020,12,7]]}}}