{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T14:13:04Z","timestamp":1771337584063,"version":"3.50.1"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"1","funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/N031962\/1"],"award-info":[{"award-number":["EP\/N031962\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Seventh Framework Programme (BE)","award":["305815"],"award-info":[{"award-number":["305815"]}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/M020576\/1"],"award-info":[{"award-number":["EP\/M020576\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1186\/s12859-017-1729-2","type":"journal-article","created":{"date-parts":[[2017,6,30]],"date-time":"2017-06-30T09:18:12Z","timestamp":1498814292000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers"],"prefix":"10.1186","volume":"18","author":[{"given":"Nicola","family":"Lazzarini","sequence":"first","affiliation":[]},{"given":"Jaume","family":"Bacardit","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,6,30]]},"reference":[{"issue":"3","key":"1729_CR1","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1067\/mcp.2001.113989","volume":"69","author":"BDW Group","year":"2001","unstructured":"Group BDW. Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001; 69(3):89\u201395. doi: 10.1067\/mcp.2001.113989 .","journal-title":"Clin Pharmacol Ther"},{"key":"1729_CR2","volume-title":"Bioinformatics Methods in Clinical Research. Methods in Molecular Biology","author":"IN Inza","year":"2010","unstructured":"Inza IN, Calvo B, Arma\u00f1anzas R, Bengoetxea E, Larra\u00f1aga P, Lozano J. Machine learning: An indispensable tool in bioinformatics. In: Bioinformatics Methods in Clinical Research. Methods in Molecular Biology. Springer: Humana Press: 2010. p. 25\u201348."},{"issue":"3","key":"1729_CR3","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1093\/bioinformatics\/btp630","volume":"26","author":"T Abeel","year":"2010","unstructured":"Abeel T, Helleputte T, Van de Peer Y, Dupont P, Saeys Y. Robust biomarker identification for cancer diagnosis with ensemble feature selection methods. Bioinformatics. 2010; 26(3):392\u20138. doi: 10.1093\/bioinformatics\/btp630 . http:\/\/arxiv.org\/abs\/http:\/\/bioinformatics.oxfordjournals.org\/content\/26\/3\/392.full.pdf+html.","journal-title":"Bioinformatics"},{"issue":"1","key":"1729_CR4","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.compbiolchem.2004.11.001","volume":"29","author":"Y Wang","year":"2005","unstructured":"Wang Y, Tetko IV, Hall MA, Frank E, Facius A, Mayer KFX, Mewes HW. Gene selection from microarray data for cancer classification\u2014a machine learning approach. Comput Biol Chem. 2005; 29(1):37\u201346. doi: 10.1016\/j.compbiolchem.2004.11.001 .","journal-title":"Comput Biol Chem"},{"issue":"1","key":"1729_CR5","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1186\/1471-2105-15-49","volume":"15","author":"KH Chen","year":"2014","unstructured":"Chen KH, Wang KJ, Tsai ML, Wang KM, Adrian AM, Cheng WC, Yang TS, Teng NC, Tan KP, Chang KS. Gene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithm. BMC Bioinforma. 2014; 15(1):49.","journal-title":"BMC Bioinforma"},{"key":"1729_CR6","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.ins.2014.05.042","volume":"282","author":"V Bol\u00f3n-Canedo","year":"2014","unstructured":"Bol\u00f3n-Canedo V, S\u00e1nchez-Maro\u00f1o N, Alonso-Betanzos A, Ben\u00edtez JM, Herrera F. A review of microarray datasets and applied feature selection methods. Inform Sci. 2014; 282:111\u201335. doi: 10.1016\/j.ins.2014.05.042 .","journal-title":"Inform Sci"},{"key":"1729_CR7","volume-title":"Correlation-based feature subset selection for machine learning. PhD thesis","author":"MA Hall","year":"1998","unstructured":"Hall MA. Correlation-based feature subset selection for machine learning. PhD thesis. Hamilton: University of Waikato; 1998."},{"issue":"8","key":"1729_CR8","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"H Peng","year":"2005","unstructured":"Peng H, Long F, Ding C. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell. 2005; 27(8):1226\u201338. doi: 10.1109\/tpami.2005.159 .","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1\u20133","key":"1729_CR9","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","volume":"46","author":"I Guyon","year":"2002","unstructured":"Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. Mach Learn. 2002; 46(1\u20133):389\u2013422.","journal-title":"Mach Learn"},{"key":"1729_CR10","doi-asserted-by":"crossref","unstructured":"Pang H, George SL, Hui K, Tong T. Gene selection using iterative feature elimination random forests for survival outcomes. IEEE\/ACM Trans Comput Biol Bioinforma. 2012; 9(5):1422\u201331. doi: 10.1109\/TCBB.2012.63 .","DOI":"10.1109\/TCBB.2012.63"},{"key":"1729_CR11","doi-asserted-by":"crossref","unstructured":"Bedo J, Sanderson C, Kowalczyk A. An efficient alternative to svm based recursive feature elimination with applications in natural language processing and bioinformatics. In: AI 2006: Advances in Artificial Intelligence. Lecture Notes in Computer Science. Springer: 2006. p. 170\u201380.","DOI":"10.1007\/11941439_21"},{"issue":"1","key":"1729_CR12","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1186\/1471-2105-8-144","volume":"8","author":"M Yousef","year":"2007","unstructured":"Yousef M, Jung S, Showe LC, Showe MK. Recursive cluster elimination (rce) for classification and feature selection from gene expression data. BMC Bioinforma. 2007; 8(1):144.","journal-title":"BMC Bioinforma"},{"issue":"Suppl 1","key":"1729_CR13","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/1471-2164-16-S1-S2","volume":"16","author":"AL Swan","year":"2015","unstructured":"Swan AL, Stekel DJ, Hodgman C, Allaway D, Alqahtani MH, Mobasheri A, Bacardit J. A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data. BMC Genomics. 2015; 16(Suppl 1):2. doi: 10.1186\/1471-2164-16-S1-S2 .","journal-title":"BMC Genomics"},{"issue":"8","key":"1729_CR14","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1109\/TNNLS.2012.2199516","volume":"23","author":"JG Moreno-Torres","year":"2012","unstructured":"Moreno-Torres JG, S\u00e1ez JA, Herrera F. Study on the impact of partition-induced dataset shift on k -fold cross-validation. IEEE Trans Neural Netw Learn Syst. 2012; 23(8):1304\u201312.","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"1","key":"1729_CR15","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s12293-008-0005-4","volume":"1","author":"J Bacardit","year":"2009","unstructured":"Bacardit J, Burke E, Krasnogor N. Improving the scalability of rule-based evolutionary learning. Memetic Comput. 2009; 1(1):55\u201367. doi: 10.1007\/s12293-008-0005-4 .","journal-title":"Memetic Comput"},{"issue":"1","key":"1729_CR16","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L. Random forests. Mach Learn. 2001; 45(1):5\u201332. doi: 10.1023\/A:1010933404324 .","journal-title":"Mach Learn"},{"key":"1729_CR17","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E. Scikit-learn: Machine learning in Python. J Mach Learn Res. 2011; 12:2825\u201330.","journal-title":"J Mach Learn Res"},{"key":"1729_CR18","doi-asserted-by":"crossref","unstructured":"O\u2019Hara S, Wang K, Slayden R, Schenkel A, Huber G, O\u2019Hern C, Shattuck M, Kirby M. Iterative feature removal yields highly discriminative pathways. BMC Genomics. 2013;14(1). doi: 10.1186\/1471-2164-14-832 .","DOI":"10.1186\/1471-2164-14-832"},{"key":"1729_CR19","doi-asserted-by":"crossref","unstructured":"Kononenko I, \u0160imec E, Robnik-\u0160ikonja M. Overcoming the myopia of inductive learning algorithms with RELIEFF Applied Intelligence, vol. 7: Springer; 1997, pp. 39\u201355.","DOI":"10.1023\/A:1008280620621"},{"key":"1729_CR20","unstructured":"Liu H, Setiono R. Chi2: Feature selection and discretization of numeric attributes. In: Proceedings of the Seventh International Conference on Tools with Artificial Intelligence. TAI \u201995. Washington, DC: IEEE Computer Society: 1995. p. 88. http:\/\/dl.acm.org\/citation.cfm?id=832245.832359 ."},{"key":"1729_CR21","unstructured":"Jaiantilal A, Grudic G, Liu H, Motoda H, Setiono R, Zhao Z. JMLR Workshop and Conference Proceedings Volume 10: Feature Selection in Data Mining. In: Proceedings of the Fourth International Workshop on Feature Selection in Data Mining. Hyderabad: 2010."},{"key":"1729_CR22","doi-asserted-by":"crossref","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH. The weka data mining software: An update. SIGKDD Explor Newsl. 2009;11(1).:10\u201318. doi: 10.1145\/1656274.1656278 .","DOI":"10.1145\/1656274.1656278"},{"issue":"3","key":"1729_CR23","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1007\/s10115-012-0487-8","volume":"34","author":"V Bol\u00f3n-Canedo","year":"2013","unstructured":"Bol\u00f3n-Canedo V, S\u00e1nchez-Maro\u00f1o N, Alonso-Betanzos A. A review of feature selection methods on synthetic data. Knowl Inform Syst. 2013; 34(3):483\u2013519. doi: 10.1007\/s10115-012-0487-8 .","journal-title":"Knowl Inform Syst"},{"key":"1729_CR24","doi-asserted-by":"crossref","unstructured":"Kim G, Kim Y, Lim H, Kim H. An mlp-based feature subset selection for hiv-1 protease cleavage site analysis. Artif Intell Med. 2010; 48(2\u20133):83\u20139. doi: 10.1016\/j.artmed.2009.07.010 . Artificial Intelligence in Biomedical Engineering and Informatics","DOI":"10.1016\/j.artmed.2009.07.010"},{"key":"1729_CR25","unstructured":"Thrun S, Bala J, Bloedorn E, Bratko I, Cestnik B, Cheng J, Jong KD, Dzeroski S, Hamann R, Kaufman K, Keller S, Kononenko I, Kreuziger J, Michalski RS, Mitchell T, Pachowicz P, Roger B, Vafaie H, de Velde WV, Wenzel W, Wnek J, Zhang J. The MONK\u2019s problems: A performance comparison of different learning algorithms. Technical Report CMU-CS-91-197, Carnegie Mellon University, Computer Science Department, Pittsburgh, PA. 1991."},{"issue":"1","key":"1729_CR26","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/1471-2105-7-3","volume":"7","author":"R D\u00edaz-Uriarte","year":"2006","unstructured":"D\u00edaz-Uriarte R, Alvarez de Andr\u00e9s S. Gene selection and classification of microarray data using random forest. BMC Bioinforma. 2006; 7(1):3. doi: 10.1186\/1471-2105-7-3 .","journal-title":"BMC Bioinforma"},{"key":"1729_CR27","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-35488-8","volume-title":"Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)","author":"I Guyon","year":"2006","unstructured":"Guyon I, Gunn S, Nikravesh M, Zadeh LA. Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing). Secaucus: Springer; 2006."},{"issue":"2","key":"1729_CR28","doi-asserted-by":"crossref","first-page":"115","DOI":"10.3390\/microarrays2020115","volume":"2","author":"D Demb\u00e9l\u00e9","year":"2013","unstructured":"Demb\u00e9l\u00e9 D. A flexible microarray data simulation model. Microarrays. 2013; 2(2):115\u201330. doi: 10.3390\/microarrays2020115 .","journal-title":"Microarrays"},{"key":"1729_CR29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/095281300146272","volume":"12","author":"X Zeng","year":"2000","unstructured":"Zeng X, Martinez TR. Distribution-balanced stratified cross-validation for accuracy estimation. J Exp Theor Artif Intell. 2000; 12:1\u201312.","journal-title":"J Exp Theor Artif Intell"},{"key":"1729_CR30","doi-asserted-by":"crossref","unstructured":"Singh D, Febbo PG, Ross K, Jackson DG, Manola J, Ladd C, Tamayo P, Renshaw AA, D\u2019Amico AV, Richie JP, Lander ES, Loda M, Kantoff PW, Golub TR, Sellers WR. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell. 2002; 1(2):203\u20139. doi: 10.1016\/S1535-6108(02)00030-2 .","DOI":"10.1016\/S1535-6108(02)00030-2"},{"key":"1729_CR31","doi-asserted-by":"crossref","unstructured":"Rappaport N, Nativ N, Stelzer G, Twik M, Guan-Golan Y, Iny Stein T, Bahir I, Belinky F, Morrey CP, Safran M, Lancet D. Malacards: an integrated compendium for diseases and their annotation. Database. 2013;2013. doi: 10.1093\/database\/bat018 .","DOI":"10.1093\/database\/bat018"},{"issue":"1","key":"1729_CR32","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1093\/nar\/30.1.52","volume":"30","author":"A Hamosh","year":"2002","unstructured":"Hamosh A, Scott AF, Amberger JS, Bocchini CA, Mckusick VA. Online mendelian inheritance in man (omim), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 2002; 30(1):52\u20135.","journal-title":"Nucleic Acids Res"},{"key":"1729_CR33","unstructured":"Orphanet. Orphanet: an Online Database of Rare Diseases and Orphan Drugs. Copyright, INSERM 1997. 1997. http:\/\/www.orpha.net . Accessed 30 Apr 2015."},{"key":"1729_CR34","doi-asserted-by":"crossref","unstructured":"Magrane M, Consortium U. Uniprot knowledgebase: a hub of integrated protein data. Database. 2011;2011. doi: 10.1093\/database\/bar009 .","DOI":"10.1093\/database\/bar009"},{"issue":"D1","key":"1729_CR35","doi-asserted-by":"crossref","first-page":"914","DOI":"10.1093\/nar\/gku935","volume":"43","author":"AP Davis","year":"2014","unstructured":"Davis AP, Grondin CJ, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Wiegers TC, Mattingly CJ. The comparative toxicogenomics database\u2019s 10th year anniversary: update 2015. Nucleic Acids Res. 2014; 43(D1):914\u201320. doi: 10.1093\/nar\/gku935 .","journal-title":"Nucleic Acids Res"},{"issue":"5","key":"1729_CR36","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1158\/2159-8290.CD-12-0095","volume":"2","author":"E Cerami","year":"2012","unstructured":"Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML, Larsson E, Antipin Y, Reva B, Goldberg AP, Sander C, Schultz N. The cbio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012; 2(5):401\u20134. doi: 10.1158\/2159-8290.CD-12-0095 .","journal-title":"Cancer Discov"},{"issue":"2","key":"1729_CR37","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1515\/sagmb-2014-0045","volume":"14","author":"N Vlassis","year":"2015","unstructured":"Vlassis N, Glaab E. Genepen: analysis of network activity alterations in complex diseases via the pairwise elastic net. Stat Appl Genet Mol Biol. 2015; 14(2):221\u20134.","journal-title":"Stat Appl Genet Mol Biol"},{"key":"1729_CR38","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"},{"issue":"2","key":"1729_CR39","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s10549-010-1073-y","volume":"128","author":"H Habashy","year":"2011","unstructured":"Habashy H, Powe D, Glaab E, Ball G, Spiteri I, Krasnogor N, Garibaldi J, Rakha E, Green A, Caldas C, Ellis I. Rerg (ras-like, oestrogen-regulated, growth-inhibitor) expression in breast cancer: a marker of er-positive luminal-like subtype. Breast Cancer Res Treat. 2011; 128(2):315\u201326. doi: 10.1007\/s10549-010-1073-y .","journal-title":"Breast Cancer Res Treat"},{"issue":"5","key":"1729_CR40","doi-asserted-by":"crossref","first-page":"1849","DOI":"10.1182\/blood-2003-02-0578","volume":"102","author":"T Yagi","year":"2003","unstructured":"Yagi T, Morimoto A, Eguchi M, Hibi S, Sako M, Ishii E, Mizutani S, Imashuku S, Ohki M, Ichikawa H. Identification of a gene expression signature associated with pediatric aml prognosis. Blood. 2003; 102(5):1849\u201356. doi: 10.1182\/blood-2003-02-0578 .","journal-title":"Blood"},{"issue":"2","key":"1729_CR41","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1002\/pros.10284","volume":"57","author":"J Luo","year":"2003","unstructured":"Luo J, Dunn TA, Ewing CM, Walsh PC, Isaacs WB. Decreased gene expression of steroid 5 alpha-reductase 2 in human prostate cancer: Implications for finasteride therapy of prostate carcinoma. The Prostate. 2003; 57(2):134\u20139. doi: 10.1002\/pros.10284 .","journal-title":"The Prostate"},{"issue":"5","key":"1729_CR42","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1177\/002215540104900517","volume":"49","author":"AG DiLella","year":"2001","unstructured":"DiLella AG, Toner TJ, Austin CP, Connolly BM. Identification of genes differentially expressed in benign prostatic hyperplasia. J Histochem Cytochem. 2001; 49(5):669\u201370. doi: 10.1177\/002215540104900517 . http:\/\/arxiv.org\/abs\/http:\/\/jhc.sagepub.com\/content\/49\/5\/669.full.pdf+html.","journal-title":"J Histochem Cytochem"},{"issue":"1","key":"1729_CR43","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1186\/1476-4598-2-34","volume":"2","author":"AG Banerjee","year":"2003","unstructured":"Banerjee AG, Liu J, Yuan Y, Gopalakrishnan VK, Johansson SL, Dinda AK, Gupta NP, Trevino L, Vishwanatha JK. Expression of biomarkers modulating prostate cancer angiogenesis: differential expression of annexin ii in prostate carcinomas from india and usa. Mol Cancer. 2003; 2(1):34.","journal-title":"Mol Cancer"},{"issue":"1","key":"1729_CR44","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s10585-012-9494-0","volume":"30","author":"L Walker","year":"2013","unstructured":"Walker L, Millena AC, Strong N, Khan SA. Expression of tgf \u03b23 and its effects on migratory and invasive behavior of prostate cancer cells: involvement of pi3-kinase\/akt signaling pathway. Clin Exp Metastasis. 2013; 30(1):13\u201323.","journal-title":"Clin Exp Metastasis"},{"issue":"6","key":"1729_CR45","doi-asserted-by":"crossref","first-page":"66278","DOI":"10.1371\/journal.pone.0066278","volume":"8","author":"DM Altintas","year":"2013","unstructured":"Altintas DM, Allioli N, Decaussin M, de Bernard S, Ruffion A. Differentially expressed androgen-regulated genes in androgen-sensitive tissues reveal potential biomarkers of early prostate cancer. PloS One. 2013; 8(6):66278.","journal-title":"PloS One"},{"key":"1729_CR46","doi-asserted-by":"crossref","unstructured":"Guyon I, Fritsche H, Choppa P, Yang LY, Barnhill S. A four-gene expression signature for prostate cancer cells consisting of UAP1, PDLIM5, IMPDH2, and HSPD1. UroToday Int J. 2009;02(04). doi: 10.3834\/uij.1944-5784.2009.08.06 .","DOI":"10.3834\/uij.1944-5784.2009.08.06"},{"issue":"7","key":"1729_CR47","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1517\/14728222.12.7.845","volume":"12","author":"DB Bernkopf","year":"2008","unstructured":"Bernkopf DB, Williams ED. Potential role of epb41l3 (protein 4.1b\/dal-1) as a target for treatment of advanced prostate cancer. Exp Opin Ther Targets. 2008; 12(7):845\u201353. doi: 10.1517\/14728222.12.7.845 .","journal-title":"Exp Opin Ther Targets"},{"issue":"9","key":"1729_CR48","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1101\/gr.772403","volume":"13","author":"PD Thomas","year":"2003","unstructured":"Thomas PD, Campbell MJ, Kejariwal A, Mi H, Karlak B, Daverman R, Diemer K, Muruganujan A, Narechania A. PANTHER: A library of protein families and subfamilies indexed by function. Genome Res. 2003; 13(9):2129\u201341. doi: 10.1101\/gr.772403 .","journal-title":"Genome Res"},{"key":"1729_CR49","doi-asserted-by":"crossref","unstructured":"Kelly P, Stemmle LN, Madden JF, Fields TA, Daaka Y, Casey PJ. A role for the g12 family of heterotrimeric g proteins in prostate cancer invasion. J Biol Chem. 2006; 281(36):26483\u201390. doi: 10.1074\/jbc.M604376200 . http:\/\/arxiv.org\/abs\/http:\/\/www.jbc.org\/content\/281\/36\/26483.full.pdf+html .","DOI":"10.1074\/jbc.M604376200"},{"issue":"216","key":"1729_CR50","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1126\/stke.2162004re2","volume":"2004","author":"Y Daaka","year":"2004","unstructured":"Daaka Y. G proteins in cancer: The prostate cancer paradigm. Sci Signaling. 2004; 2004(216):2\u20132. doi: 10.1126\/stke.2162004re2 . http:\/\/arxiv.org\/abs\/http:\/\/stke.sciencemag.org\/content\/2004\/216\/re2.full.pdf.","journal-title":"Sci Signaling"},{"issue":"7286","key":"1729_CR51","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1038\/nature08782","volume":"464","author":"M Ammirante","year":"2010","unstructured":"Ammirante M, Luo JL, Grivennikov S, Nedospasov S, Karin M. B-cell-derived lymphotoxin promotes castration-resistant prostate cancer. Nature. 2010; 464(7286):302\u20135.","journal-title":"Nature"},{"issue":"1","key":"1729_CR52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1479-5876-12-1","volume":"12","author":"JR Woo","year":"2014","unstructured":"Woo JR, Liss MA, Muldong MT, Palazzi K, Strasner A, Ammirante M, Varki N, Shabaik A, Howell S, Kane CJ, et al. Tumor infiltrating b-cells are increased in prostate cancer tissue. J Trans Med. 2014; 12(1):1.","journal-title":"J Trans Med"},{"issue":"2","key":"1729_CR53","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s40259-015-0122-9","volume":"29","author":"V Hillerdal","year":"2015","unstructured":"Hillerdal V, Essand M. Chimeric antigen receptor-engineered t cells for the treatment of metastatic prostate cancer. BioDrugs. 2015; 29(2):75\u201389. doi: 10.1007\/s40259-015-0122-9 .","journal-title":"BioDrugs"},{"issue":"8","key":"1729_CR54","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1093\/bioinformatics\/btp101","volume":"25","author":"G Bindea","year":"2009","unstructured":"Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, Fridman WH, Pag\u00e8s F, Trajanoski Z, Galon J. Cluego: a cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009; 25(8):1091\u20133.","journal-title":"Bioinformatics"},{"issue":"18","key":"1729_CR55","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1093\/bioinformatics\/bts389","volume":"28","author":"E Glaab","year":"2012","unstructured":"Glaab E, Baudot A, Krasnogor N, Schneider R, Valencia A. Enrichnet: network-based gene set enrichment analysis. Bioinformatics. 2012; 28(18):451\u20137. doi: 10.1093\/bioinformatics\/bts389 .","journal-title":"Bioinformatics"},{"key":"1729_CR56","first-page":"1","volume":"2012","author":"G Rodr\u00edguez-Berriguete","year":"2011","unstructured":"Rodr\u00edguez-Berriguete G, Fraile B, Mart\u00ednez-Onsurbe P, Olmedilla G, Paniagua R, Royuela M. Map kinases and prostate cancer. J Signal Trans. 2011; 2012:1\u20139.","journal-title":"J Signal Trans"},{"key":"1729_CR57","doi-asserted-by":"crossref","unstructured":"Svetnik V, Liaw A, Tong C, Wang T. Application of breiman\u2019s random forest to modeling structure-activity relationships of pharmaceutical molecules. In: Multiple Classifier Systems. Lecture Notes in Computer Science. Springer: 2004. p. 334\u201343.","DOI":"10.1007\/978-3-540-25966-4_33"},{"key":"1729_CR58","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/1755-8794-3-8","volume":"3","author":"A Sboner","year":"2010","unstructured":"Sboner A, Demichelis F, Calza S, Pawitan Y, Setlur SR, Hoshida Y, Perner S, Adami HO, Fall K, Mucci LA, Kantoff PW, Stampfer M, Andersson SO, Varenhorst E, Johansson JE, Gerstein MB, Golub TR, Rubin MA, Andr\u00e9n O. Molecular sampling of prostate cancer: a dilemma for predicting disease progression. BMC Med Genomics. 2010; 3:8. doi: 10.1186\/1755-8794-3-8 .","journal-title":"BMC Med Genomics"},{"issue":"1","key":"1729_CR59","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/nm0102-68","volume":"8","author":"MA Shipp","year":"2002","unstructured":"Shipp MA, Ross KN, Tamayo P, Weng AP, Kutok JL, Aguiar RC, Gaasenbeek M, Angelo M, Reich M, Pinkus GS, Ray TS, Koval MA, Last KW, Norton A, Lister TA, Mesirov J, Neuberg DS, Lander ES, Aster JC, Golub TR. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med. 2002; 8(1):68\u201374. doi: 10.1038\/nm0102-68 .","journal-title":"Nat Med"},{"issue":"6870","key":"1729_CR60","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/415436a","volume":"415","author":"SL Pomeroy","year":"2002","unstructured":"Pomeroy SL, Tamayo P, Gaasenbeek M, Sturla LM, Angelo M, McLaughlin ME, Kim JYH, Goumnerova LC, Black PM, Lau C, Allen JC, Zagzag D, Olson JM, Curran T, Wetmore C, Biegel JA, Poggio T, Mukherjee S, Rifkin R, Califano A, Stolovitzky G, Louis DN, Mesirov JP, Lander ES, Golub TR. Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature. 2002; 415(6870):436\u201342. doi: 10.1038\/415436a .","journal-title":"Nature"},{"issue":"5439","key":"1729_CR61","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","volume":"286","author":"TR Golub","year":"1999","unstructured":"Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science. 1999; 286(5439):531\u20137. doi: 10.1126\/science.286.5439.531 . http:\/\/arxiv.org\/abs\/http:\/\/www.sciencemag.org\/content\/286\/5439\/531.full.pdf.","journal-title":"Science"},{"issue":"1","key":"1729_CR62","doi-asserted-by":"crossref","first-page":"31","DOI":"10.2353\/jmoldx.2006.050056","volume":"8","author":"D Chowdary","year":"2006","unstructured":"Chowdary D, Lathrop J, Skelton J, Curtin K, Briggs T, Zhang Y, Yu J, Wang Y, Mazumder A. Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative. J Mol Diag. 2006; 8(1):31\u20139. doi: 10.2353\/jmoldx.2006.050056 .","journal-title":"J Mol Diag"},{"issue":"1","key":"1729_CR63","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/1476-4598-9-3","volume":"9","author":"WJ Kim","year":"2010","unstructured":"Kim WJ, Kim EJ, Kim SK, Kim YJ, Ha YS, Jeong P, Kim MJ, Yun SJ, Lee KM, Moon SK, et al. Predictive value of progression-related gene classifier in primary non-muscle invasive bladder cancer. Mol Cancer. 2010; 9(1):3.","journal-title":"Mol Cancer"},{"issue":"88","key":"1729_CR64","first-page":"2016","volume":"55","author":"L Badea","year":"2008","unstructured":"Badea L, Herlea V, Dima SO, Dumitrascu T, Popescu I. Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia-the authors reported a combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia. Hepato-gastroenterology. 2008; 55(88):2016.","journal-title":"Hepato-gastroenterology"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-017-1729-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,27]],"date-time":"2019-09-27T20:23:52Z","timestamp":1569615832000},"score":1,"resource":{"primary":{"URL":"http:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-017-1729-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,30]]},"references-count":64,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["1729"],"URL":"https:\/\/doi.org\/10.1186\/s12859-017-1729-2","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,6,30]]},"article-number":"322"}}