{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T10:55:41Z","timestamp":1771584941985,"version":"3.50.1"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"S5","license":[{"start":{"date-parts":[[2018,11,1]],"date-time":"2018-11-01T00:00:00Z","timestamp":1541030400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Syst Biol"],"published-print":{"date-parts":[[2018,11]]},"DOI":"10.1186\/s12918-018-0612-8","type":"journal-article","created":{"date-parts":[[2018,11,20]],"date-time":"2018-11-20T08:54:53Z","timestamp":1542704093000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["BLASSO: integration of biological knowledge into a regularized linear model"],"prefix":"10.1186","volume":"12","author":[{"given":"Daniel","family":"Urda","sequence":"first","affiliation":[]},{"given":"Francisco","family":"Arag\u00f3n","sequence":"additional","affiliation":[]},{"given":"Roc\u00edo","family":"Bautista","sequence":"additional","affiliation":[]},{"given":"Leonardo","family":"Franco","sequence":"additional","affiliation":[]},{"given":"Francisco J.","family":"Veredas","sequence":"additional","affiliation":[]},{"given":"Manuel Gonzalo","family":"Claros","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9 Manuel","family":"Jerez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,11,20]]},"reference":[{"issue":"7573","key":"612_CR1","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1038\/nature15816","volume":"526","author":"SJ Aronson","year":"2015","unstructured":"Aronson SJ, Rehm HL. Building the foundation for genomics in precision medicine. Nature. 2015; 526(7573):336\u201342. https:\/\/doi.org\/10.1038\/nature15816 .","journal-title":"Nature"},{"issue":"4","key":"612_CR2","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1016\/j.molcel.2015.05.004","volume":"58","author":"J Reuter","year":"2015","unstructured":"Reuter J, Spacek DV, Snyder M. High-throughput sequencing technologies. Mol Cell. 2015; 58(4):586\u201397. https:\/\/doi.org\/10.1016\/j.molcel.2015.05.004 .","journal-title":"Mol Cell"},{"issue":"6","key":"612_CR3","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1002\/bies.200900181","volume":"32","author":"M Kircher","year":"2010","unstructured":"Kircher M, Kelso J. High-throughput dna sequencing \u2013 concepts and limitations. BioEssays. 2010; 32(6):524\u201336. https:\/\/doi.org\/10.1002\/bies.200900181 .","journal-title":"BioEssays"},{"issue":"1906","key":"612_CR4","doi-asserted-by":"publisher","first-page":"4237","DOI":"10.1098\/rsta.2009.0159","volume":"367","author":"IM Johnstone","year":"2009","unstructured":"Johnstone IM, Titterington DM. Statistical challenges of high-dimensional data. Philos T Roy Soc A. 2009; 367(1906):4237\u201353. https:\/\/doi.org\/10.1098\/rsta.2009.0159 .","journal-title":"Philos T Roy Soc A"},{"key":"612_CR5","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/j.neunet.2012.02.016","volume":"32","author":"J Stallkamp","year":"2012","unstructured":"Stallkamp J, Schlipsing M, Salmen J, Igel C. Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. Neural Netw. 2012; 32:323\u201332. https:\/\/doi.org\/10.1016\/j.neunet.2012.02.016 .","journal-title":"Neural Netw"},{"issue":"1","key":"612_CR6","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s10994-013-5375-2","volume":"95","author":"C Perlich","year":"2014","unstructured":"Perlich C, Dalessandro B, Raeder T, Stitelman O, Provost F. Machine learning for targeted display advertising: transfer learning in action. Mach Learn. 2014; 95(1):103\u201327. https:\/\/doi.org\/10.1007\/s10994-013-5375-2 .","journal-title":"Mach Learn"},{"issue":"7553","key":"612_CR7","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1038\/nature14541","volume":"521","author":"Z Ghahramani","year":"2015","unstructured":"Ghahramani Z. Probabilistic machine learning and artificial intelligence. Nature. 2015; 521(7553):452\u20139. https:\/\/doi.org\/10.1038\/nature14541 .","journal-title":"Nature"},{"key":"612_CR8","doi-asserted-by":"crossref","unstructured":"Deng L, Hinton G, Kingsbury B. New types of deep neural network learning for speech recognition and related applications: An overview. In: Proc Int Conf Acoust Speech Signal Process: 2013.","DOI":"10.1109\/ICASSP.2013.6639344"},{"issue":"8","key":"612_CR9","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1109\/34.31448","volume":"11","author":"K Fukunaga","year":"1989","unstructured":"Fukunaga K, Hayes RR. Effects of sample size in classifier design. IEEE Trans Pattern Anal Mach Intell. 1989; 11(8):873\u201385.","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"612_CR10","volume-title":"Proceedings of the Fourth Australian Knowledge Acquisition Workshop (AKAW-99)","author":"D Brain","year":"1999","unstructured":"Brain D, Webb GI. On the effect of data set size on bias and variance in classification learning In: Richards D, Beydoun G, Hoffmann A, Compton P, editors. Proceedings of the Fourth Australian Knowledge Acquisition Workshop (AKAW-99). Sydney: The University of New South Wales: 1999. p. 117\u201328."},{"issue":"19","key":"612_CR11","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1093\/bioinformatics\/btm344","volume":"23","author":"Y Saeys","year":"2007","unstructured":"Saeys Y, Inza I, Larra\u00f1aga P. A review of feature selection techniques in bioinformatics. Bioinformatics. 2007; 23(19):2507.","journal-title":"Bioinformatics"},{"key":"612_CR12","doi-asserted-by":"crossref","unstructured":"Schirra L-R, Lausser L, Kestler HA. In: Wilhelm AFX, Kestler HA, (eds).Selection Stability as a Means of Biomarker Discovery in Classification: Springer International Publishing; 2016. pp. 79\u201389.","DOI":"10.1007\/978-3-319-25226-1_7"},{"issue":"6871","key":"612_CR13","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1038\/415530a","volume":"415","author":"LJ van \u2019t Veer","year":"2002","unstructured":"van \u2019t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002; 415(6871):530\u20136. https:\/\/doi.org\/10.1038\/415530a .","journal-title":"Nature"},{"issue":"9460","key":"612_CR14","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1016\/S0140-6736(05)70933-8","volume":"365","author":"Y Wang","year":"2005","unstructured":"Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J, Jatkoe T, Berns EM, Atkins D, Foekens JA. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer,. Lancet. 2005; 365(9460):671\u20139. https:\/\/doi.org\/10.1016\/s0140-6736(05)17947-1 .","journal-title":"Lancet"},{"issue":"10","key":"612_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pcbi.1002240","volume":"7","author":"D Venet","year":"2011","unstructured":"Venet D, Dumont JE, Detours V. Most random gene expression signatures are significantly associated with breast cancer outcome. PLoS Comput Biol. 2011; 7(10):1\u20138. https:\/\/doi.org\/10.1371\/journal.pcbi.1002240 .","journal-title":"PLoS Comput Biol"},{"key":"612_CR16","first-page":"336","volume":"8","author":"I Saez","year":"2014","unstructured":"Saez I, Set E, Hsu M. From genes to behavior: placing cognitive models in the context of biological pathways. Front Neurosci-Switz. 2014; 8:336.","journal-title":"Front Neurosci-Switz"},{"key":"612_CR17","unstructured":"Vellido A, Mart\u00edn-guerrero J, Lisboa PJG. Making machine learning models interpretable. In: Proc. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: 2012."},{"issue":"1","key":"612_CR18","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1186\/1471-2105-14-5","volume":"14","author":"L Song","year":"2013","unstructured":"Song L, Langfelder P, Horvath S. Random generalized linear model: a highly accurate and interpretable ensemble predictor. BMC Bioinformatics. 2013; 14(1):5.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"612_CR19","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1080\/23808993.2016.1142826","volume":"1","author":"B Tomlinson","year":"2016","unstructured":"Tomlinson B, Hu M, Waye MMY, Chan P, Liu Z-M. Current status of personalized medicine based on pharmacogenetics in cardiovascular medicine. Expert Rev Precis Med Drug Dev. 2016; 1(1):5\u20138.","journal-title":"Expert Rev Precis Med Drug Dev"},{"issue":"3","key":"612_CR20","first-page":"150","volume":"55","author":"S Mirsadeghi","year":"2017","unstructured":"Mirsadeghi S, Larijani B. Personalized medicine: Pharmacogenomics and drug development. Acta Medica Iran. 2017; 55(3):150\u201365.","journal-title":"Acta Medica Iran"},{"issue":"W1","key":"612_CR21","doi-asserted-by":"publisher","first-page":"W518","DOI":"10.1093\/nar\/gkt441","volume":"41","author":"Chih-Hsuan Wei","year":"2013","unstructured":"Wei C-H, Kao H-Y, Lu Z. Pubtator: a web-based text mining tool for assisting biocuration. Nucleic Acids Res. 2013;41. https:\/\/doi.org\/10.1093\/nar\/gkt441 .","journal-title":"Nucleic Acids Research"},{"issue":"0","key":"612_CR22","doi-asserted-by":"publisher","first-page":"bas041","DOI":"10.1093\/database\/bas041","volume":"2012","author":"C.-H. Wei","year":"2012","unstructured":"Wei C-H, Harris BR, Li D, Berardini TZ, Huala E, Kao H-Y, Lu Z. Accelerating literature curation with text-mining tools: a case study of using pubtator to curate genes in pubmed abstracts. Database. 2012; 18. https:\/\/doi.org\/10.1093\/database\/bas041 .","journal-title":"Database"},{"key":"612_CR23","doi-asserted-by":"crossref","unstructured":"Wei C-H, Kao H-Y, Lu Z. Pubtator: A pubmed-like interactive curation system for document triage and literature curation. In: Proceedings of BioCreative 2012 Workshop. Washington DC: 2012. p. 145\u201350.","DOI":"10.1093\/database\/bas041"},{"issue":"1","key":"612_CR24","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1186\/1471-2105-12-323","volume":"12","author":"B Li","year":"2011","unstructured":"Li B, Dewey CN. Rsem: accurate transcript quantification from rna-seq data with or without a reference genome. BMC Bioinformatics. 2011; 12(1):323. https:\/\/doi.org\/10.1186\/1471-2105-12-323 .","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"612_CR25","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani R. Regression shrinkage and selection via the lasso: a retrospective. J R Stat Soc B). 1996; 58(1):267\u201388.","journal-title":"J R Stat Soc B)"},{"issue":"476","key":"612_CR26","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1198\/016214506000000735","volume":"101","author":"H Zou","year":"2006","unstructured":"Zou H. The Adaptive Lasso and Its Oracle Properties. J Am Stat Assoc. 2006; 101(476):1418\u201329.","journal-title":"J Am Stat Assoc"},{"issue":"1","key":"612_CR27","doi-asserted-by":"publisher","first-page":"33","DOI":"10.18547\/gcb.2016.vol2.iss1.e33","volume":"2","author":"J Fontaine","year":"2016","unstructured":"Fontaine J, Andrade-Navarro M. Gene set to diseases (gs2d): Disease enrichment analysis on human gene sets with literature data. Genomics Comput Biol. 2016; 2(1):33.","journal-title":"Genomics Comput Biol"},{"issue":"1","key":"612_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v033.i01","volume":"33","author":"J Friedman","year":"2010","unstructured":"Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010; 33(1):1\u201322.","journal-title":"J Stat Softw"},{"key":"612_CR29","doi-asserted-by":"publisher","first-page":"1895","DOI":"10.1162\/089976698300017197","volume":"10","author":"TG Dietterich","year":"1998","unstructured":"Dietterich TG. Approximate statistical tests for comparing supervised classification learning algorithms. Neural Computat. 1998; 10:1895\u2013923.","journal-title":"Neural Computat"},{"key":"612_CR30","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J. Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res. 2006; 7:1\u201330.","journal-title":"J Mach Learn Res"},{"key":"612_CR31","unstructured":"Lacoste A, Laviolette F, Marchand M. Bayesian comparison of machine learning algorithms on single and multiple datasets. In: Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, vol. 22: 2012. p. 665\u201375."},{"key":"612_CR32","first-page":"1089","volume":"5","author":"Y Bengio","year":"2004","unstructured":"Bengio Y, Grandvalet Y. No unbiased estimator of the variance of k-fold cross-validation. J Mach Learn Res. 2004; 5:1089\u2013105.","journal-title":"J Mach Learn Res"},{"issue":"1","key":"612_CR33","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1186\/1756-0500-5-87","volume":"5","author":"I Stoimenov","year":"2012","unstructured":"Stoimenov I, Lagerqvist A. The pcna pseudogenes in the human genome. BMC Research Notes. 2012; 5(1):87. https:\/\/doi.org\/10.1186\/1756-0500-5-87 .","journal-title":"BMC Research Notes"},{"key":"612_CR34","doi-asserted-by":"crossref","unstructured":"Lian Y, Xu Y, Xiao C, Xia R, Gong H, Yang P, Chen T, Wu D, Cai Z, Zhang J, Wang K. The pseudogene derived from long non-coding RNA DUXAP10 promotes colorectal cancer cell growth through epigenetically silencing of p21 and PTEN. Sci Rep. 2017; 7(1). https:\/\/doi.org\/10.1038\/s41598-017-07954-7 .","DOI":"10.1038\/s41598-017-07954-7"}],"container-title":["BMC Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-018-0612-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12918-018-0612-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-018-0612-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T15:40:54Z","timestamp":1720798854000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcsystbiol.biomedcentral.com\/articles\/10.1186\/s12918-018-0612-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11]]},"references-count":34,"journal-issue":{"issue":"S5","published-print":{"date-parts":[[2018,11]]}},"alternative-id":["612"],"URL":"https:\/\/doi.org\/10.1186\/s12918-018-0612-8","relation":{},"ISSN":["1752-0509"],"issn-type":[{"value":"1752-0509","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11]]},"assertion":[{"value":"20 November 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Publisher\u2019s Note"}}],"article-number":"94"}}