{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T04:38:35Z","timestamp":1771475915971,"version":"3.50.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"S4","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Syst Biol"],"published-print":{"date-parts":[[2016,12]]},"DOI":"10.1186\/s12918-016-0358-0","type":"journal-article","created":{"date-parts":[[2016,12,23]],"date-time":"2016-12-23T11:37:42Z","timestamp":1482493062000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["High-dimensional omics data analysis using a variable screening protocol with prior knowledge integration (SKI)"],"prefix":"10.1186","volume":"10","author":[{"given":"Cong","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianlei","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhangsheng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,12,23]]},"reference":[{"issue":"14","key":"358_CR1","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1093\/jnci\/93.14.1054","volume":"93","author":"MS Pepe","year":"2001","unstructured":"Pepe MS, et al. Phases of biomarker development for early detection of cancer. J Natl Cancer Inst. 2001;93(14):1054\u201361.","journal-title":"J Natl Cancer Inst"},{"issue":"10","key":"358_CR2","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1001\/archneurol.2012.1282","volume":"69","author":"JD Doecke","year":"2012","unstructured":"Doecke JD, et al. Blood-based protein biomarkers for diagnosis of Alzheimer disease. Arch Neurol. 2012;69(10):1318\u201325.","journal-title":"Arch Neurol"},{"issue":"7","key":"358_CR3","doi-asserted-by":"crossref","first-page":"1646","DOI":"10.1002\/ijc.29172","volume":"136","author":"B Zheng","year":"2015","unstructured":"Zheng B, et al. A three-gene panel that distinguishes benign from malignant thyroid nodules. Int J Cancer. 2015;136(7):1646\u201354.","journal-title":"Int J Cancer"},{"key":"358_CR4","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.jtbi.2014.06.038","volume":"362","author":"JL Gu","year":"2014","unstructured":"Gu JL, et al. Multiclass classification of sarcomas using pathway based feature selection method. J Theor Biol. 2014;362:3\u20138.","journal-title":"J Theor Biol"},{"issue":"5","key":"358_CR5","doi-asserted-by":"crossref","first-page":"1368","DOI":"10.1158\/1078-0432.CCR-07-1658","volume":"14","author":"MC Cheang","year":"2008","unstructured":"Cheang MC, et al. Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin Cancer Res. 2008;14(5):1368\u201376.","journal-title":"Clin Cancer Res"},{"issue":"8","key":"358_CR6","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1200\/JCO.2008.18.1370","volume":"27","author":"JS Parker","year":"2009","unstructured":"Parker JS, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160\u20137.","journal-title":"J Clin Oncol"},{"issue":"1","key":"358_CR7","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.clpt.2005.10.002","volume":"79","author":"SC Sim","year":"2006","unstructured":"Sim SC, et al. A common novel CYP2C19 gene variant causes ultrarapid drug metabolism relevant for the drug response to proton pump inhibitors and antidepressants. Clin Pharmacol Ther. 2006;79(1):103\u201313.","journal-title":"Clin Pharmacol Ther"},{"issue":"3","key":"358_CR8","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1097\/FPC.0b013e32834fdd41","volume":"22","author":"S Aslibekyan","year":"2012","unstructured":"Aslibekyan S, et al. A genome-wide association study of inflammatory biomarker changes in response to fenofibrate treatment in the Genetics of Lipid Lowering Drug and Diet Network. Pharmacogenet Genomics. 2012;22(3):191\u20137.","journal-title":"Pharmacogenet Genomics"},{"issue":"8","key":"358_CR9","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1592\/phco.28.8.992","volume":"28","author":"FW Frueh","year":"2008","unstructured":"Frueh FW, et al. Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use. Pharmacotherapy. 2008;28(8):992\u20138.","journal-title":"Pharmacotherapy"},{"issue":"16","key":"358_CR10","doi-asserted-by":"crossref","first-page":"9440","DOI":"10.1073\/pnas.1530509100","volume":"100","author":"JD Storey","year":"2003","unstructured":"Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci U S A. 2003;100(16):9440\u20135.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"3","key":"358_CR11","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1093\/bioinformatics\/btf877","volume":"19","author":"A Reiner","year":"2003","unstructured":"Reiner A, Yekutieli D, Benjamini Y. Identifying differentially expressed genes using false discovery rate controlling procedures. Bioinformatics. 2003;19(3):368\u201375.","journal-title":"Bioinformatics"},{"key":"358_CR12","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"1","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc Ser B Methodol. 1996;1:267\u201388.","journal-title":"J R Stat Soc Ser B Methodol"},{"issue":"476","key":"358_CR13","doi-asserted-by":"crossref","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":"456","key":"358_CR14","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1198\/016214501753382273","volume":"96","author":"J Fan","year":"2001","unstructured":"Fan J, Li R. Variable selection via nonconcave penalized likelihood and its oracle properties. J Am Stat Assoc. 2001;96(456):1348\u201360.","journal-title":"J Am Stat Assoc"},{"issue":"5","key":"358_CR15","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1111\/j.1467-9868.2008.00674.x","volume":"70","author":"J Fan","year":"2008","unstructured":"Fan J, Lv J. Sure independence screening for ultrahigh dimensional feature space. J R Stat Soc Ser B (Stat Methodol). 2008;70(5):849\u2013911.","journal-title":"J R Stat Soc Ser B (Stat Methodol)"},{"issue":"1","key":"358_CR16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2202\/1544-6115.1438","volume":"8","author":"RJ Tibshirani","year":"2009","unstructured":"Tibshirani RJ. Univariate shrinkage in the Cox model for high dimensional data. Stat Appl Genet Mol Biol. 2009;8(1):1\u201318.","journal-title":"Stat Appl Genet Mol Biol"},{"issue":"22","key":"358_CR17","doi-asserted-by":"crossref","first-page":"2906","DOI":"10.1093\/bioinformatics\/btp543","volume":"25","author":"R Shen","year":"2009","unstructured":"Shen R, Olshen AB, Ladanyi M. Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis. Bioinformatics. 2009;25(22):2906\u201312.","journal-title":"Bioinformatics"},{"issue":"1","key":"358_CR18","doi-asserted-by":"crossref","first-page":"e53014","DOI":"10.1371\/journal.pone.0053014","volume":"8","author":"MR Aure","year":"2013","unstructured":"Aure MR, et al. Identifying in-trans process associated genes in breast cancer by integrated analysis of copy number and expression data. PLoS One. 2013;8(1):e53014.","journal-title":"PLoS One"},{"issue":"6","key":"358_CR19","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1016\/j.cell.2010.11.013","volume":"143","author":"UD Akavia","year":"2010","unstructured":"Akavia UD, et al. An integrated approach to uncover drivers of cancer. Cell. 2010;143(6):1005\u201317.","journal-title":"Cell"},{"issue":"12","key":"358_CR20","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1038\/nbt.2877","volume":"32","author":"JC Costello","year":"2014","unstructured":"Costello JC, et al. A community effort to assess and improve drug sensitivity prediction algorithms. Nat Biotechnol. 2014;32(12):1202\u201312.","journal-title":"Nat Biotechnol"},{"issue":"9875","key":"358_CR21","doi-asserted-by":"crossref","first-page":"1371","DOI":"10.1016\/S0140-6736(12)62129-1","volume":"381","author":"Consortium, C.-D.G.o.t.P.G","year":"2013","unstructured":"Consortium, C.-D.G.o.t.P.G. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381(9875):1371\u20139.","journal-title":"Lancet"},{"issue":"9","key":"358_CR22","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1038\/ng.2711","volume":"45","author":"Consortium, C.-D.G.o.t.P.G","year":"2013","unstructured":"Consortium, C.-D.G.o.t.P.G. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet. 2013;45(9):984\u201394.","journal-title":"Nat Genet"},{"issue":"suppl 1","key":"358_CR23","doi-asserted-by":"crossref","first-page":"i180","DOI":"10.1093\/bioinformatics\/btg1023","volume":"19","author":"J-D Kim","year":"2003","unstructured":"Kim J-D, et al. GENIA corpus-a semantically annotated corpus for bio-textmining. Bioinformatics. 2003;19 suppl 1:i180\u20132.","journal-title":"Bioinformatics"},{"issue":"2","key":"358_CR24","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1038\/nrg1768","volume":"7","author":"LJ Jensen","year":"2006","unstructured":"Jensen LJ, Saric J, Bork P. Literature mining for the biologist: from information retrieval to biological discovery. Nat Rev Genet. 2006;7(2):119\u201329.","journal-title":"Nat Rev Genet"},{"issue":"1","key":"358_CR25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-15-68","volume":"15","author":"HG Roider","year":"2014","unstructured":"Roider HG, et al. Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network. BMC Bioinf. 2014;15(1):1.","journal-title":"BMC Bioinf"},{"key":"358_CR26","doi-asserted-by":"crossref","first-page":"2313","DOI":"10.1214\/009053606000001523","volume":"35","author":"E Candes","year":"2007","unstructured":"Candes E, Tao T. The Dantzig selector: statistical estimation when p is much larger than n. Ann Stat. 2007;35:2313\u201351.","journal-title":"Ann Stat"},{"issue":"2","key":"358_CR27","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Ser B (Stat Methodol). 2005;67(2):301\u201320.","journal-title":"J R Stat Soc Ser B (Stat Methodol)"},{"key":"358_CR28","doi-asserted-by":"crossref","first-page":"191","DOI":"10.2307\/2347628","volume":"41","author":"S Cessie Le","year":"1992","unstructured":"Le Cessie S, Van JC. Houwelingen, Ridge estimators in logistic regression. Appl Stat. 1992;41:191\u2013201.","journal-title":"Appl Stat"},{"key":"358_CR29","first-page":"btu396","volume":"30","author":"Y Zheng","year":"2014","unstructured":"Zheng Y, et al. PGS: a tool for association study of high-dimensional microRNA expression data with repeated measures. Bioinformatics. 2014;30:btu396.","journal-title":"Bioinformatics"},{"issue":"1","key":"358_CR30","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1186\/1471-2105-13-168","volume":"13","author":"R Song","year":"2012","unstructured":"Song R, Huang J, Ma S. Integrative prescreening in analysis of multiple cancer genomic studies. BMC Bioinf. 2012;13(1):168.","journal-title":"BMC Bioinf"},{"issue":"1","key":"358_CR31","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1042\/BST20110647","volume":"40","author":"AS Little","year":"2012","unstructured":"Little AS, et al. Tumour cell responses to MEK1\/2 inhibitors: acquired resistance and pathway remodelling. Biochem Soc Trans. 2012;40(1):73\u20138.","journal-title":"Biochem Soc Trans"},{"issue":"6","key":"358_CR32","doi-asserted-by":"crossref","first-page":"2264","DOI":"10.1158\/0008-5472.CAN-09-1577","volume":"70","author":"JR Dry","year":"2010","unstructured":"Dry JR, et al. Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244). Cancer Res. 2010;70(6):2264\u201373.","journal-title":"Cancer Res"},{"issue":"24","key":"358_CR33","doi-asserted-by":"crossref","first-page":"6716","DOI":"10.1158\/1078-0432.CCR-13-0842","volume":"19","author":"HK Bid","year":"2013","unstructured":"Bid HK, et al. Development, characterization, and reversal of acquired resistance to the MEK1 inhibitor selumetinib (AZD6244) in an in vivo model of childhood astrocytoma. Clin Cancer Res. 2013;19(24):6716\u201329.","journal-title":"Clin Cancer Res"},{"issue":"12","key":"358_CR34","doi-asserted-by":"crossref","first-page":"3351","DOI":"10.1158\/1535-7163.MCT-10-0376","volume":"9","author":"JJ Tentler","year":"2010","unstructured":"Tentler JJ, et al. Identification of Predictive Markers of Response to the MEK1\/2 Inhibitor Selumetinib (AZD6244) in K-ras-Mutated Colorectal Cancer. Mol Cancer Ther. 2010;9(12):3351\u201362.","journal-title":"Mol Cancer Ther"},{"issue":"7391","key":"358_CR35","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1038\/nature11003","volume":"483","author":"J Barretina","year":"2012","unstructured":"Barretina J, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483(7391):603\u20137.","journal-title":"Nature"},{"issue":"1","key":"358_CR36","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0004-3702(02)00190-X","volume":"137","author":"Z-H Zhou","year":"2002","unstructured":"Zhou Z-H, Wu J, Tang W. Ensembling neural networks: many could be better than all. Artif Intell. 2002;137(1):239\u201363.","journal-title":"Artif Intell"},{"issue":"1","key":"358_CR37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2202\/1544-6115.1703","volume":"10","author":"LC Bergersen","year":"2011","unstructured":"Bergersen LC, Glad IK, Lyng H. Weighted lasso with data integration. Stat Appl Genet Mol Biol. 2011;10(1):1\u201329.","journal-title":"Stat Appl Genet Mol Biol"},{"issue":"3","key":"358_CR38","doi-asserted-by":"crossref","first-page":"1846","DOI":"10.1214\/12-AOS1024","volume":"40","author":"G Li","year":"2012","unstructured":"Li G, et al. Robust rank correlation based screening. Ann Stat. 2012;40(3):1846\u201377.","journal-title":"Ann Stat"}],"container-title":["BMC Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-016-0358-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T11:12:49Z","timestamp":1718968369000},"score":1,"resource":{"primary":{"URL":"http:\/\/bmcsystbiol.biomedcentral.com\/articles\/10.1186\/s12918-016-0358-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12]]},"references-count":38,"journal-issue":{"issue":"S4","published-print":{"date-parts":[[2016,12]]}},"alternative-id":["358"],"URL":"https:\/\/doi.org\/10.1186\/s12918-016-0358-0","relation":{},"ISSN":["1752-0509"],"issn-type":[{"value":"1752-0509","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,12]]},"article-number":"118"}}