{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T01:50:15Z","timestamp":1764813015029,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In recent years, the Ribosome profiling technique (Ribo\u2013seq) has emerged as a powerful method for globally monitoring the translation process in vivo at single nucleotide resolution. Based on deep sequencing of mRNA fragments, Ribo\u2013seq allows to obtain profiles that reflect the time spent by ribosomes in translating each part of an open reading frame. Unfortunately, the profiles produced by this method can vary significantly in different experimental setups, being characterized by a poor reproducibility. To address this problem, we have employed a statistical method for the identification of highly reproducible Ribo\u2013seq profiles, which was tested on a set of E. coli genes. State-of-the-art artificial neural network models have been used to validate the quality of the produced sequences. Moreover, new insights into the dynamics of ribosome translation have been provided through a statistical analysis on the obtained sequences.<\/jats:p>","DOI":"10.3390\/a15080274","type":"journal-article","created":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T21:52:48Z","timestamp":1659649968000},"page":"274","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Neural Network Approach for the Analysis of Reproducible Ribo\u2013Seq Profiles"],"prefix":"10.3390","volume":"15","author":[{"given":"Giorgia","family":"Giacomini","sequence":"first","affiliation":[{"name":"San Raffaele Telethon Institute for Gene Therapy, IRCCS San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7606-9405","authenticated-orcid":false,"given":"Caterina","family":"Graziani","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics (DIISM), University of Siena, 53100 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6947-7304","authenticated-orcid":false,"given":"Veronica","family":"Lachi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics (DIISM), University of Siena, 53100 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9074-0587","authenticated-orcid":false,"given":"Pietro","family":"Bongini","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics (DIISM), University of Siena, 53100 Siena, Italy"},{"name":"Department of Computer Science, University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa, Italy"},{"name":"Department of Information Engineering, University of Florence, Via S. Marta 3, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2212-4728","authenticated-orcid":false,"given":"Niccol\u00f2","family":"Pancino","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics (DIISM), University of Siena, 53100 Siena, Italy"},{"name":"Department of Information Engineering, University of Florence, Via S. Marta 3, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8206-8142","authenticated-orcid":false,"given":"Monica","family":"Bianchini","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics (DIISM), University of Siena, 53100 Siena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2752-3189","authenticated-orcid":false,"given":"Davide","family":"Chiarugi","sequence":"additional","affiliation":[{"name":"Bioinformatics and Biostatistics Core, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Addenbrooke\u2019s Treatment Centre, Keith Day Road, Cambridge CB2 0QQ, UK"}]},{"given":"Angelo","family":"Valleriani","sequence":"additional","affiliation":[{"name":"Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany"}]},{"given":"Paolo","family":"Andreini","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Mathematics (DIISM), University of Siena, 53100 Siena, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"367","DOI":"10.3389\/fgene.2018.00367","article-title":"mTOR signaling, translational control, and the circadian clock","volume":"9","author":"Cao","year":"2018","journal-title":"Front. 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