{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T12:06:10Z","timestamp":1784030770902,"version":"3.55.0"},"reference-count":83,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,11,15]],"date-time":"2016-11-15T00:00:00Z","timestamp":1479168000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2016,11,15]],"date-time":"2016-11-15T00:00:00Z","timestamp":1479168000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["RF1AG054014-01"],"award-info":[{"award-number":["RF1AG054014-01"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["U01AG052411"],"award-info":[{"award-number":["U01AG052411"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["U01AI111598-01"],"award-info":[{"award-number":["U01AI111598-01"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA163772"],"award-info":[{"award-number":["R01CA163772"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Syst Biol"],"published-print":{"date-parts":[[2016,12]]},"DOI":"10.1186\/s12918-016-0349-1","type":"journal-article","created":{"date-parts":[[2016,11,15]],"date-time":"2016-11-15T12:04:49Z","timestamp":1479211489000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":223,"title":["DGCA: A comprehensive R package for Differential Gene Correlation Analysis"],"prefix":"10.1186","volume":"10","author":[{"given":"Andrew T.","family":"McKenzie","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor","family":"Katsyv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Won-Min","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minghui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2016,11,15]]},"reference":[{"key":"349_CR1","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/S0065-2660(07)00421-X","volume":"60","author":"J Zhu","year":"2008","unstructured":"Zhu J, Zhang B, Schadt EE. A systems biology approach to drug discovery. Adv Genet. 2008;60:603\u201335.","journal-title":"Adv Genet"},{"key":"349_CR2","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/gm2","volume":"1","author":"C Auffray","year":"2009","unstructured":"Auffray C, Chen Z, Hood L. Systems medicine: the future of medical genomics and healthcare. Genome Med. 2009;1:2.","journal-title":"Genome Med"},{"key":"349_CR3","doi-asserted-by":"publisher","first-page":"R106","DOI":"10.1186\/gb-2010-11-10-r106","volume":"11","author":"S Anders","year":"2010","unstructured":"Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106.","journal-title":"Genome Biol"},{"key":"349_CR4","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1186\/gb-2003-4-4-210","volume":"4","author":"X Cui","year":"2003","unstructured":"Cui X, Churchill GA. Statistical tests for differential expression in cDNA microarray experiments. Genome Biol. 2003;4:210.","journal-title":"Genome Biol"},{"key":"349_CR5","doi-asserted-by":"crossref","first-page":"Article17","DOI":"10.2202\/1544-6115.1128","volume":"4","author":"B Zhang","year":"2005","unstructured":"Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol. 2005;4:Article17.","journal-title":"Stat Appl Genet Mol Biol"},{"key":"349_CR6","doi-asserted-by":"publisher","first-page":"e1004574","DOI":"10.1371\/journal.pcbi.1004574","volume":"11","author":"W-M Song","year":"2015","unstructured":"Song W-M, Zhang B. Multiscale Embedded Gene Co-expression Network Analysis. PLoS Comput Biol. 2015;11:e1004574.","journal-title":"PLoS Comput Biol"},{"key":"349_CR7","doi-asserted-by":"publisher","first-page":"e1001057","DOI":"10.1371\/journal.pcbi.1001057","volume":"7","author":"P Langfelder","year":"2011","unstructured":"Langfelder P, Luo R, Oldham MC, Horvath S. Is my network module preserved and reproducible? PLoS Comput Biol. 2011;7:e1001057.","journal-title":"PLoS Comput Biol"},{"key":"349_CR8","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1016\/j.cell.2013.03.030","volume":"153","author":"B Zhang","year":"2013","unstructured":"Zhang B, Gaiteri C, Bodea L-G, Wang Z, McElwee J, Podtelezhnikov AA, Zhang C, Xie T, Tran L, Dobrin R, et al. Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer\u2019s Disease. Cell. 2013;153:707\u201320.","journal-title":"Cell"},{"key":"349_CR9","doi-asserted-by":"publisher","first-page":"743","DOI":"10.15252\/msb.20145304","volume":"10","author":"M Narayanan","year":"2014","unstructured":"Narayanan M, Huynh JL, Wang K, Yang X, Yoo S, McElwee J, Zhang B, Zhang C, Lamb JR, Xie T, et al. Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases. Mol Syst Biol. 2014;10:743.","journal-title":"Mol Syst Biol"},{"key":"349_CR10","doi-asserted-by":"publisher","first-page":"e1002955","DOI":"10.1371\/journal.pcbi.1002955","volume":"9","author":"D Amar","year":"2013","unstructured":"Amar D, Safer H, Shamir R. Dissection of regulatory networks that are altered in disease via differential co-expression. PLoS Comput Biol. 2013;9:e1002955.","journal-title":"PLoS Comput Biol"},{"key":"349_CR11","doi-asserted-by":"publisher","first-page":"btv406","DOI":"10.1093\/bioinformatics\/btv406","volume":"31","author":"MJ Ha","year":"2015","unstructured":"Ha MJ, Baladandayuthapani V, Do K-A. DINGO: Differential Network Analysis in Genomics. Bioinformatics. 2015;31:btv406.","journal-title":"Bioinformatics"},{"key":"349_CR12","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1186\/1471-2105-7-509","volume":"7","author":"M Watson","year":"2006","unstructured":"Watson M. CoXpress: differential co-expression in gene expression data. BMC Bioinformatics. 2006;7:509.","journal-title":"BMC Bioinformatics"},{"key":"349_CR13","series-title":"Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing","first-page":"145","volume-title":"Subspace differential coexpression analysis: problem definition and a general approach","author":"G Fang","year":"2010","unstructured":"Fang G, Kuang R, Pandey G, Steinbach M, Myers CL, Kumar V. Subspace differential coexpression analysis: problem definition and a general approach, Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing. 2010. p. 145\u201356."},{"key":"349_CR14","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1186\/1471-2105-11-497","volume":"11","author":"BM Tesson","year":"2010","unstructured":"Tesson BM, Breitling R, Jansen RC. DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules. BMC Bioinformatics. 2010;11:497.","journal-title":"BMC Bioinformatics"},{"key":"349_CR15","doi-asserted-by":"publisher","first-page":"2780","DOI":"10.1093\/bioinformatics\/btp502","volume":"25","author":"Y Choi","year":"2009","unstructured":"Choi Y, Kendziorski C. Statistical methods for gene set co-expression analysis. Bioinformatics. 2009;25:2780\u20136.","journal-title":"Bioinformatics"},{"key":"349_CR16","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1093\/bioinformatics\/btt687","volume":"30","author":"Y Rahmatallah","year":"2014","unstructured":"Rahmatallah Y, Emmert-Streib F, Glazko G. Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets. Bioinformatics. 2014;30:360\u20138.","journal-title":"Bioinformatics"},{"key":"349_CR17","doi-asserted-by":"publisher","first-page":"3146","DOI":"10.1093\/bioinformatics\/bth379","volume":"20","author":"Y Lai","year":"2004","unstructured":"Lai Y, Wu B, Chen L, Zhao H. A statistical method for identifying differential gene-gene co-expression patterns. Bioinformatics. 2004;20:3146\u201355.","journal-title":"Bioinformatics"},{"key":"349_CR18","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.gene.2012.11.028","volume":"518","author":"A Fukushima","year":"2013","unstructured":"Fukushima A. DiffCorr: an R package to analyze and visualize differential correlations in biological networks. Gene. 2013;518:209\u201314.","journal-title":"Gene"},{"key":"349_CR19","doi-asserted-by":"publisher","first-page":"1939","DOI":"10.1093\/bioinformatics\/bts268","volume":"28","author":"JA Dawson","year":"2012","unstructured":"Dawson JA, Ye S, Kendziorski C. R\/EBcoexpress: an empirical Bayesian framework for discovering differential co-expression. Bioinformatics. 2012;28:1939\u201340.","journal-title":"Bioinformatics"},{"key":"349_CR20","doi-asserted-by":"crossref","unstructured":"Siska C, Bowler R, Kechris K. The Discordant Method: A Novel Approach for Differential Correlation. Bioinformatics. 2016;32:690\u201396.","DOI":"10.1093\/bioinformatics\/btv633"},{"key":"349_CR21","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1093\/bioinformatics\/btm103","volume":"23","author":"Y Lai","year":"2007","unstructured":"Lai Y, Adam B-l, Podolsky R, She J-X. A mixture model approach to the tests of concordance and discordance between two large-scale experiments with two-sample groups. Bioinformatics. 2007;23:1243\u201350.","journal-title":"Bioinformatics"},{"key":"349_CR22","first-page":"507","volume":"10","author":"RA Fisher","year":"1915","unstructured":"Fisher RA. Frequency Distribution of the Values of the Correlation Coefficient in Samples from an Indefinitely Large Population. Biometrika. 1915;10:507\u201321.","journal-title":"Biometrika"},{"key":"349_CR23","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1177\/1536867X0800800307","volume":"8","author":"NJ Cox","year":"2008","unstructured":"Cox NJ. Speaking Stata: Correlation with confidence, or Fisher\u2019s z revisited. Stata J. 2008;8:413\u201339.","journal-title":"Stata J"},{"key":"349_CR24","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1093\/biomet\/44.3-4.470","volume":"44","author":"EC Fieller","year":"1957","unstructured":"Fieller EC, Hartley HO, Pearson ES. Tests for Rank Correlation Coefficients. I. Biometrika. 1957;44:470\u201381.","journal-title":"Biometrika"},{"key":"349_CR25","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc Ser B Methodol. 1995;57:289\u2013300.","journal-title":"J R Stat Soc Ser B Methodol"},{"key":"349_CR26","first-page":"1064","volume":"224","author":"JD Storey","year":"2003","unstructured":"Storey JD, Tibshirani R. Statistical methods for identifying differentially expressed genes in DNA microarrays. Methods Mol Biol. 2003;224:1064\u20133745. (Print)):149-157.","journal-title":"Methods Mol Biol"},{"key":"349_CR27","doi-asserted-by":"publisher","first-page":"1461","DOI":"10.1093\/bioinformatics\/btn209","volume":"24","author":"K Strimmer","year":"2008","unstructured":"Strimmer K. fdrtool: a versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics. 2008;24:1461\u20132.","journal-title":"Bioinformatics"},{"key":"349_CR28","volume-title":"qvalue: Q-value estimation for false discovery rate control","author":"J Storey","year":"2015","unstructured":"Storey J. qvalue: Q-value estimation for false discovery rate control. 2015."},{"key":"349_CR29","doi-asserted-by":"publisher","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;100:9440\u20135.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"349_CR30","first-page":"280","volume-title":"Statistical Methods for Psychology","author":"DC Howell","year":"2012","unstructured":"Howell DC. Statistical Methods for Psychology. 2012. p. 280\u20131."},{"key":"349_CR31","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1186\/1471-2164-12-98","volume":"12","author":"CC Mason","year":"2011","unstructured":"Mason CC, Hanson RL, Ossowski V, Bian L, Baier LJ, Krakoff J, Bogardus C. Bimodal distribution of RNA expression levels in human skeletal muscle tissue. BMC Genomics. 2011;12:98.","journal-title":"BMC Genomics"},{"key":"349_CR32","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.neuron.2015.11.013","volume":"89","author":"Y Zhang","year":"2015","unstructured":"Zhang Y, Sloan Steven A, Clarke Laura E, Caneda C, Plaza Colton A, Blumenthal Paul D, Vogel H, Steinberg Gary K, Edwards Michael SB, Li G, et al. Purification and Characterization of Progenitor and Mature Human Astrocytes Reveals Transcriptional and Functional Differences with Mouse. Neuron. 2015;89:37\u201353.","journal-title":"Neuron"},{"key":"349_CR33","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-21706-2","volume-title":"Modern Applied Statistics with S","author":"WN Venables","year":"2002","unstructured":"Venables WN, Ripley BD. Modern Applied Statistics with S. 2002."},{"key":"349_CR34","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1186\/1471-2105-12-77","volume":"12","author":"X Robin","year":"2011","unstructured":"Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, M\u00fcller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.","journal-title":"BMC Bioinformatics"},{"key":"349_CR35","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1038\/nature11412","volume":"490","author":"DC Koboldt","year":"2012","unstructured":"Koboldt DC, Fulton RS, McLellan MD, Schmidt H, Kalicki-Veizer J, McMichael JF, Fulton LL, Dooling DJ, Ding L, Mardis ER, et al. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490:61\u201370.","journal-title":"Nature"},{"key":"349_CR36","doi-asserted-by":"publisher","first-page":"8612","DOI":"10.1128\/MCB.22.24.8612-8625.2002","volume":"22","author":"A Inga","year":"2002","unstructured":"Inga A, Storici F, Darden TA, Resnick MA. Differential transactivation by the p53 transcription factor is highly dependent on p53 level and promoter target sequence. Mol Cell Biol. 2002;22:8612\u201325.","journal-title":"Mol Cell Biol"},{"key":"349_CR37","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1016\/j.cels.2015.12.004","volume":"1","author":"A Liberzon","year":"2015","unstructured":"Liberzon A, Birger C, Thorvaldsd\u00f3ttir H, Ghandi M, Mesirov Jill P, Tamayo P. The Molecular Signatures Database Hallmark Gene Set Collection. Cell Systems. 2015;1:417\u201325.","journal-title":"Cell Systems"},{"key":"349_CR38","doi-asserted-by":"publisher","first-page":"D674","DOI":"10.1093\/nar\/gkn653","volume":"37","author":"CF Schaefer","year":"2009","unstructured":"Schaefer CF, Anthony K, Krupa S, Buchoff J, Day M, Hannay T, Buetow KH. PID: the Pathway Interaction Database. Nucleic Acids Res. 2009;37:D674\u20139.","journal-title":"Nucleic Acids Res"},{"key":"349_CR39","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1089\/152791601750294344","volume":"2","author":"D Nishimura","year":"2001","unstructured":"Nishimura D. BioCarta. Biotech Software Internet Report. 2001;2:117\u201320.","journal-title":"Biotech Software Internet Report"},{"key":"349_CR40","doi-asserted-by":"publisher","first-page":"15545","DOI":"10.1073\/pnas.0506580102","volume":"102","author":"A Subramanian","year":"2005","unstructured":"Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102:15545\u201350.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"349_CR41","doi-asserted-by":"publisher","first-page":"D535","DOI":"10.1093\/nar\/gkj109","volume":"34","author":"C Stark","year":"2006","unstructured":"Stark C, Breitkreutz B-J, Reguly T, Boucher L, Breitkreutz A, Tyers M. BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 2006;34:D535\u20139.","journal-title":"Nucleic Acids Res"},{"key":"349_CR42","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1093\/bioinformatics\/btl567","volume":"23","author":"S Falcon","year":"2007","unstructured":"Falcon S, Gentleman R. Using GOstats to test gene lists for GO term association. Bioinformatics. 2007;23:257\u20138.","journal-title":"Bioinformatics"},{"key":"349_CR43","first-page":"70","volume-title":"Categorical Data Analysis","author":"A Agresti","year":"2012","unstructured":"Agresti A. Categorical Data Analysis. 2012. p. 70\u20137."},{"key":"349_CR44","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1186\/1471-2105-11-497","volume":"11","author":"BM Tesson","year":"2010","unstructured":"Tesson BM, Breitling R, Jansen RC, Chu S, DeRisi J, Eisen M, Mulholland J, Botstein D, Brown P, Herskowitz I, et al. DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules. BMC Bioinformatics. 2010;11:497.","journal-title":"BMC Bioinformatics"},{"key":"349_CR45","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s10549-014-2991-x","volume":"146","author":"S Haricharan","year":"2014","unstructured":"Haricharan S, Bainbridge MN, Scheet P, Brown PH. Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data. Breast Cancer Res Treat. 2014;146:211\u201320.","journal-title":"Breast Cancer Res Treat"},{"key":"349_CR46","doi-asserted-by":"publisher","first-page":"e100","DOI":"10.1038\/oncsis.2014.14","volume":"3","author":"F Al-Ejeh","year":"2014","unstructured":"Al-Ejeh F, Simpson PT, Sanus JM, Klein K, Kalimutho M, Shi W, Miranda M, Kutasovic J, Raghavendra A, Madore J, et al. Meta-analysis of the global gene expression profile of triple-negative breast cancer identifies genes for the prognostication and treatment of aggressive breast cancer. Oncogenesis. 2014;3:e100.","journal-title":"Oncogenesis"},{"key":"349_CR47","doi-asserted-by":"publisher","first-page":"D199","DOI":"10.1093\/nar\/gkt1076","volume":"42","author":"M Kanehisa","year":"2014","unstructured":"Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res. 2014;42:D199\u2013205.","journal-title":"Nucleic Acids Res"},{"key":"349_CR48","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1038\/cr.2014.71","volume":"24","author":"Q Feng","year":"2014","unstructured":"Feng Q, Zhang Z, Shea MJ, Creighton CJ, Coarfa C, Hilsenbeck SG, Lanz R, He B, Wang L, Fu X, et al. An epigenomic approach to therapy for tamoxifen-resistant breast cancer. Cell Res. 2014;24:809\u201319.","journal-title":"Cell Res"},{"key":"349_CR49","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1016\/j.ccr.2013.04.026","volume":"23","author":"G Buchwalter","year":"2013","unstructured":"Buchwalter G, Hickey Michele M, Cromer A, Selfors Laura M, Gunawardane Ruwanthi N, Frishman J, Jeselsohn R, Lim E, Chi D, Fu X, et al. PDEF Promotes Luminal Differentiation and Acts as a Survival Factor for ER-Positive Breast Cancer Cells. Cancer Cell. 2013;23:753\u201367.","journal-title":"Cancer Cell"},{"key":"349_CR50","first-page":"4115","volume":"31","author":"N Patani","year":"2011","unstructured":"Patani N, Jiang WG, Newbold RF, Mokbel K. Histone-modifier gene expression profiles are associated with pathological and clinical outcomes in human breast cancer. Anticancer Res. 2011;31:4115\u201325.","journal-title":"Anticancer Res"},{"key":"349_CR51","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1038\/onc.2013.579","volume":"34","author":"AR Daniel","year":"2015","unstructured":"Daniel AR, Gaviglio AL, Knutson TP, Ostrander JH, D\u2019Assoro AB, Ravindranathan P, Peng Y, Raj GV, Yee D, Lange CA. Progesterone receptor-B enhances estrogen responsiveness of breast cancer cells via scaffolding PELP1- and estrogen receptor-containing transcription complexes. Oncogene. 2015;34:506\u201315.","journal-title":"Oncogene"},{"key":"349_CR52","doi-asserted-by":"publisher","first-page":"e70096","DOI":"10.1371\/journal.pone.0070096","volume":"8","author":"IS Fenne","year":"2013","unstructured":"Fenne IS, Helland T, Fl\u00e5geng MH, Dankel SN, Mellgren G, Sagen JV. Downregulation of steroid receptor coactivator-2 modulates estrogen-responsive genes and stimulates proliferation of mcf-7 breast cancer cells. PLoS One. 2013;8:e70096.","journal-title":"PLoS One"},{"key":"349_CR53","doi-asserted-by":"publisher","first-page":"1268","DOI":"10.1101\/gad.190678.112","volume":"26","author":"WA Freed-Pastor","year":"2012","unstructured":"Freed-Pastor WA, Prives C. Mutant p53: one name, many proteins. Genes Dev. 2012;26:1268\u201386.","journal-title":"Genes Dev"},{"key":"349_CR54","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1038\/ncb2641","volume":"15","author":"PAJ Muller","year":"2013","unstructured":"Muller PAJ, Vousden KH. p53 mutations in cancer. Nat Cell Biol. 2013;15:2\u20138.","journal-title":"Nat Cell Biol"},{"key":"349_CR55","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/s10549-009-0657-x","volume":"123","author":"X-X Cao","year":"2009","unstructured":"Cao X-X, Xu J-D, Xu J-W, Liu X-L, Cheng Y-Y, Wang W-J, Li Q-Q, Chen Q, Xu Z-D, Liu X-P. RACK1 promotes breast carcinoma proliferation and invasion\/metastasis in vitro and in vivo. Breast Cancer Res Treat. 2009;123:375\u201386.","journal-title":"Breast Cancer Res Treat"},{"key":"349_CR56","doi-asserted-by":"publisher","first-page":"935","DOI":"10.1101\/gad.9.8.935","volume":"9","author":"KF Macleod","year":"1995","unstructured":"Macleod KF, Sherry N, Hannon G, Beach D, Tokino T, Kinzler K, Vogelstein B, Jacks T. p53-dependent and independent expression of p21 during cell growth, differentiation, and DNA damage. Genes Dev. 1995;9:935\u201344.","journal-title":"Genes Dev"},{"key":"349_CR57","doi-asserted-by":"publisher","first-page":"e1002770","DOI":"10.1371\/journal.pgen.1002770","volume":"8","author":"IM Bochkis","year":"2012","unstructured":"Bochkis IM, Schug J, Ye DZ, Kurinna S, Stratton SA, Barton MC, Kaestner KH. Genome-wide location analysis reveals distinct transcriptional circuitry by paralogous regulators Foxa1 and Foxa2. PLoS Genet. 2012;8:e1002770.","journal-title":"PLoS Genet"},{"key":"349_CR58","doi-asserted-by":"publisher","first-page":"926","DOI":"10.4161\/cc.5.9.2714","volume":"5","author":"C Yan","year":"2006","unstructured":"Yan C, Boyd DD. ATF3 regulates the stability of p53: a link to cancer. Cell Cycle (Georgetown, Tex). 2006;5:926\u20139.","journal-title":"Cell Cycle (Georgetown, Tex)"},{"key":"349_CR59","doi-asserted-by":"publisher","first-page":"8947","DOI":"10.1074\/jbc.M113.503755","volume":"289","author":"S Wei","year":"2014","unstructured":"Wei S, Wang H, Lu C, Malmut S, Zhang J, Ren S, Yu G, Wang W, Tang DD, Yan C. The activating transcription factor 3 protein suppresses the oncogenic function of mutant p53 proteins. J Biol Chem. 2014;289:8947\u201359.","journal-title":"J Biol Chem"},{"key":"349_CR60","doi-asserted-by":"publisher","first-page":"3685","DOI":"10.1172\/JCI69741","volume":"123","author":"JR Doherty","year":"2013","unstructured":"Doherty JR, Cleveland JL. Targeting lactate metabolism for cancer therapeutics. J Clin Invest. 2013;123:3685\u201392.","journal-title":"J Clin Invest"},{"key":"349_CR61","doi-asserted-by":"publisher","first-page":"948","DOI":"10.18632\/oncotarget.389","volume":"2","author":"E Madan","year":"2011","unstructured":"Madan E, Gogna R, Bhatt M, Pati U, Kuppusamy P, Mahdi AA. Regulation of glucose metabolism by p53: emerging new roles for the tumor suppressor. Oncotarget. 2011;2:948\u201357.","journal-title":"Oncotarget"},{"key":"349_CR62","first-page":"1387","volume":"34","author":"P Kechagioglou","year":"2014","unstructured":"Kechagioglou P, Papi RM, Provatopoulou X, Kalogera E, Papadimitriou E, Grigoropoulos P, Nonni A, Zografos G, Kyriakidis DA, Gounaris A. Tumor suppressor PTEN in breast cancer: heterozygosity, mutations and protein expression. Anticancer Res. 2014;34:1387\u2013400.","journal-title":"Anticancer Res"},{"key":"349_CR63","doi-asserted-by":"crossref","first-page":"625","DOI":"10.3892\/ol.2011.541","volume":"3","author":"W Wang","year":"2012","unstructured":"Wang W, Zheng Z, Yu W, Lin H, Cui B, Cao F. Polymorphisms of the FAS and FASL genes and risk of breast cancer. Oncol Lett. 2012;3:625\u20138.","journal-title":"Oncol Lett"},{"key":"349_CR64","doi-asserted-by":"publisher","first-page":"1222","DOI":"10.1128\/MCB.01660-08","volume":"29","author":"JW Peacock","year":"2009","unstructured":"Peacock JW, Palmer J, Fink D, Ip S, Pietras EM, Mui AL-F, Chung SW, Gleave ME, Cox ME, Parsons R, et al. PTEN Loss Promotes Mitochondrially Dependent Type II Fas-Induced Apoptosis via PEA-15. Mol Cell Biol. 2009;29:1222\u201334.","journal-title":"Mol Cell Biol"},{"key":"349_CR65","doi-asserted-by":"publisher","first-page":"5389","DOI":"10.1038\/sj.onc.1208555","volume":"24","author":"S Bandyopadhyay","year":"2005","unstructured":"Bandyopadhyay S, Pai SK, Watabe M, Gross SC, Hirota S, Hosobe S, Tsukada T, Miura K, Saito K, Markwell SJ, et al. FAS expression inversely correlates with PTEN level in prostate cancer and a PI 3-kinase inhibitor synergizes with FAS siRNA to induce apoptosis. Oncogene. 2005;24:5389\u201395.","journal-title":"Oncogene"},{"key":"349_CR66","doi-asserted-by":"publisher","first-page":"20281","DOI":"10.1074\/jbc.M110.109207","volume":"285","author":"D Sayed","year":"2010","unstructured":"Sayed D, He M, Hong C, Gao S, Rane S, Yang Z, Abdellatif M. MicroRNA-21 Is a Downstream Effector of AKT That Mediates Its Antiapoptotic Effects via Suppression of Fas Ligand. J Biol Chem. 2010;285:20281\u201390.","journal-title":"J Biol Chem"},{"key":"349_CR67","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.yexcr.2011.10.018","volume":"318","author":"MA Attar","year":"2012","unstructured":"Attar MA, Salem JC, Pursel HS, Santy LC. CNK3 and IPCEF1 produce a single protein that is required for HGF dependent Arf6 activation and migration. Exp Cell Res. 2012;318:228\u201337.","journal-title":"Exp Cell Res"},{"key":"349_CR68","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1186\/1471-2407-14-279","volume":"14","author":"MC Lloyd","year":"2014","unstructured":"Lloyd MC, Alfarouk KO, Verduzco D, Bui MM, Gillies RJ, Ibrahim ME, Brown JS, Gatenby RA. Vascular measurements correlate with estrogen receptor status. BMC Cancer. 2014;14:279.","journal-title":"BMC Cancer"},{"key":"349_CR69","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1016\/j.bone.2004.03.021","volume":"35","author":"F Journ\u00e9","year":"2004","unstructured":"Journ\u00e9 F, Dumon J-C, Kheddoumi N, Fox J, La\u00efos I, Leclercq G, Body J-J. Extracellular calcium downregulates estrogen receptor alpha and increases its transcriptional activity through calcium-sensing receptor in breast cancer cells. Bone. 2004;35:479\u201388.","journal-title":"Bone"},{"key":"349_CR70","doi-asserted-by":"publisher","first-page":"1658","DOI":"10.1158\/0008-5472.CAN-10-1899","volume":"71","author":"SD Divekar","year":"2011","unstructured":"Divekar SD, Storchan GB, Sperle K, Veselik DJ, Johnson E, Dakshanamurthy S, Lajiminmuhip YN, Nakles RE, Huang L, Martin MB. The role of calcium in the activation of estrogen receptor-alpha. Cancer Res. 2011;71:1658\u201368.","journal-title":"Cancer Res"},{"key":"349_CR71","doi-asserted-by":"publisher","first-page":"15162","DOI":"10.1038\/srep15162","volume":"5","author":"S Banerjee","year":"2015","unstructured":"Banerjee S, Wei Z, Tan F, Peck KN, Shih N, Feldman M, Rebbeck TR, Alwine JC, Robertson ES. Distinct microbiological signatures associated with triple negative breast cancer. Scientific Reports. 2015;5:15162.","journal-title":"Scientific Reports"},{"key":"349_CR72","doi-asserted-by":"publisher","first-page":"6025","DOI":"10.1007\/s11033-014-3480-3","volume":"41","author":"R Casadei","year":"2014","unstructured":"Casadei R, Pelleri MC, Vitale L, Facchin F, Canaider S, Strippoli P, Vian M, Piovesan A, Bianconi E, Mariani E, et al. Characterization of human gene locus CYYR1: a complex multi-transcript system. Mol Biol Rep. 2014;41:6025\u201338.","journal-title":"Mol Biol Rep"},{"key":"349_CR73","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.ctrv.2016.03.011","volume":"46","author":"MV Dieci","year":"2016","unstructured":"Dieci MV, Griguolo G, Miglietta F, Guarneri V. The immune system and hormone-receptor positive breast cancer: Is it really a dead end? Cancer Treat Rev. 2016;46:9\u201319.","journal-title":"Cancer Treat Rev"},{"key":"349_CR74","doi-asserted-by":"publisher","first-page":"2147","DOI":"10.3390\/cancers7040883","volume":"7","author":"DP Rose","year":"2015","unstructured":"Rose DP, Gracheck PJ, Vona-Davis L. The Interactions of Obesity, Inflammation and Insulin Resistance in Breast Cancer. Cancers. 2015;7:2147\u201368.","journal-title":"Cancers"},{"key":"349_CR75","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1177\/1758834012475152","volume":"5","author":"J Stagg","year":"2013","unstructured":"Stagg J, Allard B. Immunotherapeutic approaches in triple-negative breast cancer: latest research and clinical prospects. Ther Advanc Med Oncol. 2013;5:169\u201381.","journal-title":"Ther Advanc Med Oncol"},{"key":"349_CR76","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.molcel.2014.06.006","volume":"55","author":"X Han","year":"2014","unstructured":"Han X, Gui B, Xiong C, Zhao L, Liang J, Sun L, Yang X, Yu W, Si W, Yan R, et al. Destabilizing LSD1 by Jade-2 promotes neurogenesis: an antibraking system in neural development. Mol Cell. 2014;55:482\u201394.","journal-title":"Mol Cell"},{"key":"349_CR77","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1177\/1947601911408889","volume":"2","author":"N Rivlin","year":"2011","unstructured":"Rivlin N, Brosh R, Oren M, Rotter V. Mutations in the p53 Tumor Suppressor Gene: Important Milestones at the Various Steps of Tumorigenesis. Genes & Cancer. 2011;2:466\u201374.","journal-title":"Genes & Cancer"},{"key":"349_CR78","doi-asserted-by":"publisher","first-page":"a001107-a001107","DOI":"10.1101\/cshperspect.a001107","volume":"2","author":"M Oren","year":"2010","unstructured":"Oren M, Rotter V. Mutant p53 Gain-of-Function in Cancer. Cold Spring Harb Perspect Biol. 2010;2:a001107-a001107.","journal-title":"Cold Spring Harb Perspect Biol"},{"key":"349_CR79","doi-asserted-by":"publisher","first-page":"e1000382","DOI":"10.1371\/journal.pcbi.1000382","volume":"5","author":"NJ Hudson","year":"2009","unstructured":"Hudson NJ, Reverter A, Dalrymple BP. A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation. PLoS Comput Biol. 2009;5:e1000382.","journal-title":"PLoS Comput Biol"},{"issue":"Suppl 1","key":"349_CR80","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1093\/bioinformatics\/bth909","volume":"20","author":"D Kostka","year":"2004","unstructured":"Kostka D, Spang R. Finding disease specific alterations in the co-expression of genes. Bioinformatics. 2004;20 Suppl 1:194\u20139.","journal-title":"Bioinformatics"},{"key":"349_CR81","doi-asserted-by":"publisher","first-page":"12837","DOI":"10.1073\/pnas.0504609102","volume":"102","author":"JD Storey","year":"2005","unstructured":"Storey JD, Xiao W, Leek JT, Tompkins RG, Davis RW. Significance analysis of time course microarray experiments. Proc Natl Acad Sci U S A. 2005;102:12837\u201342.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"349_CR82","doi-asserted-by":"publisher","first-page":"e1004502","DOI":"10.1371\/journal.pgen.1004502","volume":"10","author":"V-P M\u00e4kinen","year":"2014","unstructured":"M\u00e4kinen V-P, Civelek M, Meng Q, Zhang B, Zhu J, Levian C, Huan T, Segr\u00e8 AV, Ghosh S, Vivar J, et al. Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease. PLoS Genet. 2014;10:e1004502.","journal-title":"PLoS Genet"},{"key":"349_CR83","doi-asserted-by":"publisher","first-page":"e1004898","DOI":"10.1371\/journal.pgen.1004898","volume":"11","author":"S Yoo","year":"2015","unstructured":"Yoo S, Takikawa S, Geraghty P, Argmann C, Campbell J, Lin L, Huang T, Tu Z, Feronjy R, Spira A, et al. Integrative Analysis of DNA Methylation and Gene Expression Data Identifies EPAS1 as a Key Regulator of COPD. PLoS Genet. 2015;11:e1004898.","journal-title":"PLoS Genet"}],"container-title":["BMC Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-016-0349-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12918-016-0349-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12918-016-0349-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T16:13:52Z","timestamp":1718900032000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcsystbiol.biomedcentral.com\/articles\/10.1186\/s12918-016-0349-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,15]]},"references-count":83,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,12]]}},"alternative-id":["349"],"URL":"https:\/\/doi.org\/10.1186\/s12918-016-0349-1","relation":{},"ISSN":["1752-0509"],"issn-type":[{"value":"1752-0509","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,11,15]]},"assertion":[{"value":"23 May 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 November 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 November 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"106"}}