{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T12:13:04Z","timestamp":1765887184236},"reference-count":73,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: There is great interest in pathway-based methods for genomics data analysis in the research community. Although machine learning methods, such as random forests, have been developed to correlate survival outcomes with a set of genes, no study has assessed the abilities of these methods in incorporating pathway information for analyzing microarray data. In general, genes that are identified without incorporating biological knowledge are more difficult to interpret. Correlating pathway-based gene expression with survival outcomes may lead to biologically more meaningful prognosis biomarkers. Thus, a comprehensive study on how these methods perform in a pathway-based setting is warranted.<\/jats:p>\n               <jats:p>Results: In this article, we describe a pathway-based method using random forests to correlate gene expression data with survival outcomes and introduce a novel bivariate node-splitting random survival forests. The proposed method allows researchers to identify important pathways for predicting patient prognosis and time to disease progression, and discover important genes within those pathways. We compared different implementations of random forests with different split criteria and found that bivariate node-splitting random survival forests with log-rank test is among the best. We also performed simulation studies that showed random forests outperforms several other machine learning algorithms and has comparable results with a newly developed component-wise Cox boosting model. Thus, pathway-based survival analysis using machine learning tools represents a promising approach in dissecting pathways and for generating new biological hypothesis from microarray studies.<\/jats:p>\n               <jats:p>Availability: R package Pwayrfsurvival is available from URL: http:\/\/www.duke.edu\/\u223chp44\/pwayrfsurvival.htm<\/jats:p>\n               <jats:p>Contact: \u00a0pathwayrf@gmail.com<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp640","type":"journal-article","created":{"date-parts":[[2009,11,19]],"date-time":"2009-11-19T01:13:16Z","timestamp":1258593196000},"page":"250-258","source":"Crossref","is-referenced-by-count":36,"title":["Pathway analysis using random forests with bivariate node-split for survival outcomes"],"prefix":"10.1093","volume":"26","author":[{"given":"Herbert","family":"Pang","sequence":"first","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27710, USA, 2 Centre de Regulacio Genomica (CRG), 08003 Barcelona, Spain, 3 Department of Epidemiology and Public Health and 4 Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520 USA"}]},{"given":"Debayan","family":"Datta","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27710, USA, 2 Centre de Regulacio Genomica (CRG), 08003 Barcelona, Spain, 3 Department of Epidemiology and Public Health and 4 Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520 USA"}]},{"given":"Hongyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27710, USA, 2 Centre de Regulacio Genomica (CRG), 08003 Barcelona, Spain, 3 Department of Epidemiology and Public Health and 4 Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520 USA"},{"name":"1 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27710, USA, 2 Centre de Regulacio Genomica (CRG), 08003 Barcelona, Spain, 3 Department of Epidemiology and Public Health and 4 Department of Genetics, Yale University School of Medicine, New Haven, CT, 06520 USA"}]}],"member":"286","published-online":{"date-parts":[[2009,11,18]]},"reference":[{"key":"2023012508221182000_B1","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1038\/nrd2397","article-title":"RAR and RXR modulation in cancer and metabolic disease","volume":"6","author":"Altucci","year":"2007","journal-title":"Nat. Rev. Drug Discov."},{"key":"2023012508221182000_B2","doi-asserted-by":"crossref","first-page":"4979","DOI":"10.1038\/sj.onc.1203869","article-title":"Expression of protein tyrosine phosphatase alpha (RPTPalpha) in human breast cancer correlates with low tumor grade, and inhibits tumor cell growth in vitro and in vivo","volume":"19","author":"Ardini","year":"2000","journal-title":"Oncogene"},{"key":"2023012508221182000_B3","first-page":"4415","article-title":"Cyclin A and E2F1 overexpression correlate with reduced disease-free survival in node-negative breast cancer patients","volume":"26","author":"Baldini","year":"2006","journal-title":"Anticancer Res."},{"key":"2023012508221182000_B4","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1023\/A:1023918026437","article-title":"Higher stromal expression of transforming growth factor-beta type II receptors is associated with poorer prognosis breast tumors","volume":"79","author":"Barlow","year":"2003","journal-title":"Breast Cancer Res. Treat."},{"key":"2023012508221182000_B5","first-page":"6931","article-title":"Prognostic significance of insulin-like growth factor 1 receptors in human breast cancer","volume":"50","author":"Bonneterre","year":"1990","journal-title":"Cancer Res."},{"key":"2023012508221182000_B6","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"2023012508221182000_B7","author":"Breiman","year":"2002","journal-title":"How to use survival forests (SFPDV1)."},{"key":"2023012508221182000_B8","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1214\/009053606000000092","article-title":"Boosting for high-dimensional linear models","volume":"34","author":"Buhlmann","year":"2006","journal-title":"Ann. Stat."},{"key":"2023012508221182000_B9","first-page":"477","article-title":"Boosting algorithms: regularization, prediction and model fitting","volume":"22","author":"Buhlmann","year":"2007","journal-title":"Stat. Sci."},{"key":"2023012508221182000_B10","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/ng1317","article-title":"Inactivation of the Wip1 phosphatase inhibits mammary tumorigenesis through p38 MAPK-mediated activation of the p16(Ink4a)-p19(Arf) pathway","volume":"36","author":"Bulavin","year":"2004","journal-title":"Nat. Genet."},{"key":"2023012508221182000_B11","doi-asserted-by":"crossref","first-page":"6615","DOI":"10.1158\/0008-5472.CAN-05-4566","article-title":"Delta9-tetrahydrocannabinol inhibits cell cycle progression in human breast cancer cells through Cdc2 regulation","volume":"66","author":"Caffarel","year":"2006","journal-title":"Cancer Res."},{"key":"2023012508221182000_B12","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/s10549-006-9323-8","article-title":"Bad expression predicts outcome in patients treated with tamoxifen","volume":"102","author":"Cannings","year":"2007","journal-title":"Breast Cancer Res. Treat."},{"key":"2023012508221182000_B13","first-page":"4805","article-title":"Transforming growth factor beta type I receptor kinase mutant associated with metastatic breast cancer","volume":"58","author":"Chen","year":"1998","journal-title":"Cancer Res."},{"key":"2023012508221182000_B14","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.jnutbio.2008.03.005","article-title":"Apigenin causes G(2)\/M arrest associated with the modulation of p21(Cip1) and Cdc2 and activates p53-dependent apoptosis pathway in human breast cancer SK-BR-3 cells","volume":"20","author":"Choi","year":"2009","journal-title":"J. Nutr. Biochem."},{"key":"2023012508221182000_B15","doi-asserted-by":"crossref","first-page":"4068","DOI":"10.1038\/sj.onc.1207568","article-title":"Genotoxic stress leads to centrosome amplification in breast cancer cell lines that have an inactive G1\/S cell cycle checkpoint","volume":"36","author":"D'Assoro","year":"2004","journal-title":"Oncogene"},{"key":"2023012508221182000_B16","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1007\/s10549-006-9382-x","article-title":"CDKN2A-positive breast cancers in young women from Poland","volume":"103","author":"Debniak","year":"2008","journal-title":"Breast Cancer Res. Treat."},{"key":"2023012508221182000_B17","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1002\/(SICI)1096-9896(199801)184:1<53::AID-PATH6>3.0.CO;2-7","article-title":"Expression of growth factors, growth-inhibiting factors, and their receptors in invasive breast cancer","volume":"184","author":"de Jong","year":"1998","journal-title":"J. Pathol."},{"key":"2023012508221182000_B18","doi-asserted-by":"crossref","first-page":"2502","DOI":"10.1038\/sj.onc.1210032","article-title":"The role of the MKK6\/p38 MAPK pathway in Wip1-dependent regulation of ErbB2-driven mammary gland tumorigenesis","volume":"26","author":"Demidov","year":"2007","journal-title":"Oncogene"},{"key":"2023012508221182000_B19","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1038\/ng1001-117","article-title":"TGF-beta signaling in tumor suppression and cancer progression","volume":"29","author":"Derynck","year":"2001","journal-title":"Nat Genet."},{"key":"2023012508221182000_B20","doi-asserted-by":"crossref","first-page":"3583","DOI":"10.1093\/bioinformatics\/bth447","article-title":"BagBoosting for tumor classification with gene expression data","volume":"20","author":"Dettling","year":"2004","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B21","author":"Efron","year":"2006","journal-title":"On testing the significance of sets of genes"},{"key":"2023012508221182000_B22","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.1038\/sj.onc.1202233","article-title":"Activation of Src in human breast tumor cell lines: elevated levels of phosphotyrosine phosphatase activity that preferentially recognizes the Src carboxy terminal negative regulatory tyrosine 530","volume":"18","author":"Egan","year":"1999","journal-title":"Oncogene"},{"key":"2023012508221182000_B23","doi-asserted-by":"crossref","first-page":"1632","DOI":"10.1093\/bioinformatics\/btn253","article-title":"Sparse kernel methods for high-dimensional survival data","volume":"15","author":"Evers","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B24","first-page":"38473","article-title":"Decorrelation of the true and estimated classifier errors in high-dimensional settings","author":"Hanczar","year":"2007","journal-title":"EURASIP J. Bioinform. Syst. Biol."},{"key":"2023012508221182000_B25","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1111\/j.0006-341X.2000.00337.x","article-title":"Time-dependent ROC curves for censored survival data and a diagnostic marker","volume":"56","author":"Heagerty","year":"2000","journal-title":"Biometrics"},{"key":"2023012508221182000_B26","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1056\/NEJM200102223440801","article-title":"Gene-expression profiles in hereditary breast cancer","volume":"344","author":"Hedenfalk","year":"2001","journal-title":"N. Engl. J. Med."},{"key":"2023012508221182000_B27","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/S0167-9473(02)00225-6","article-title":"On the exact distribution of maximally selected rank statistics","volume":"43","author":"Hothorn","year":"2003","journal-title":"Comput. Stat. Data Anal."},{"key":"2023012508221182000_B28","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1198\/106186006X133933","article-title":"Unbiased recursive partitioning: a conditional inference framework","volume":"15","author":"Hothorn","year":"2006","journal-title":"J. Comput. Graph. Stat."},{"key":"2023012508221182000_B29","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1093\/biostatistics\/kxj011","article-title":"Survival ensembles","volume":"7","author":"Hothorn","year":"2006","journal-title":"Biostatistics"},{"key":"2023012508221182000_B30","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1214\/08-AOAS169","article-title":"Random survival forests","volume":"2","author":"Ishwaran","year":"2008","journal-title":"Ann. Appl. Stat."},{"key":"2023012508221182000_B31","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1093\/bioinformatics\/btl103","article-title":"CASPAR: a hierarchical Bayesian approach to predict survival times in cancer from gene expression data","volume":"22","author":"Kaderali","year":"2006","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B32","first-page":"871","article-title":"The Hedgehog pathway is a possible therapeutic target for patients with estrogen receptor-negative breast cancer","volume":"29","author":"Kameda","year":"2009","journal-title":"Anticancer Res."},{"key":"2023012508221182000_B33","doi-asserted-by":"crossref","first-page":"D354","DOI":"10.1093\/nar\/gkj102","article-title":"From genomics to chemical genomics: new developments in KEGG","volume":"34","author":"Kanehisa","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"2023012508221182000_B34","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1038\/nature03097","article-title":"Cell-cycle checkpoints and cancer","volume":"432","author":"Kastan","year":"2004","journal-title":"Nature"},{"key":"2023012508221182000_B35","doi-asserted-by":"crossref","first-page":"2519","DOI":"10.1093\/carcin\/bgl103","article-title":"Radiation clastogenesis and cell cycle checkpoint function as functional markers of breast cancer risk","volume":"27","author":"Kaufmann","year":"2006","journal-title":"Carcinogenesis"},{"key":"2023012508221182000_B36","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1093\/bioinformatics\/btm116","article-title":"Extending the pathway analysis framework with a test for transcriptional variance implicates novel pathway modulation during myogenic differentiation","volume":"23","author":"Kemp","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B37","doi-asserted-by":"crossref","first-page":"3086","DOI":"10.1038\/sj.onc.1203632","article-title":"Human breast cancer cells contain elevated levels and activity of the protein kinase, PKR","volume":"19","author":"Kim","year":"2000","journal-title":"Oncogene"},{"issue":"Suppl. 1","key":"2023012508221182000_B38","doi-asserted-by":"crossref","first-page":"i208","DOI":"10.1093\/bioinformatics\/bth900","article-title":"Partial Cox regression analysis for high-dimensional microarray gene expression data","volume":"20","author":"Li","year":"2004","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B39","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1198\/016214505000001230","article-title":"Random forests and adaptive nearest neighbors","volume":"101","author":"Lin","year":"2006","journal-title":"J. Am. Stat. Assoc."},{"key":"2023012508221182000_B40","first-page":"482","article-title":"Inhibiting mutations in the transforming growth factor beta type 2 receptor in recurrent human breast cancer","volume":"61","author":"Lucke","year":"2001","journal-title":"Cancer Res."},{"key":"2023012508221182000_B41","doi-asserted-by":"crossref","first-page":"2797","DOI":"10.1158\/1078-0432.CCR-1073-03","article-title":"Loss of CD55 is associated with aggressive breast tumors","volume":"10","author":"Madjd","year":"2004","journal-title":"Clin. Cancer Res."},{"key":"2023012508221182000_B42","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/s00262-004-0590-0","article-title":"Do poor-prognosis breast tumours express membrane cofactor proteins (CD46)?","volume":"54","author":"Madjd","year":"2005","journal-title":"Cancer Immunol. Immunother."},{"key":"2023012508221182000_B43","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1038\/nature03094","article-title":"G1 cell-cycle control and cancer","volume":"432","author":"Massague","year":"2004","journal-title":"Nature"},{"key":"2023012508221182000_B44","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1093\/bioinformatics\/btm447","article-title":"Successful anti-cancer drug targets able to pass FDA review demonstrate the identifiable signature distinct from the signatures of random genes and initially proposed targets","volume":"24","author":"Mayburd","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B45","doi-asserted-by":"crossref","first-page":"13550","DOI":"10.1073\/pnas.0506230102","article-title":"An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival","volume":"102","author":"Miller","year":"2005","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012508221182000_B46","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/bcr552","article-title":"BAD: a good therapeutic target?","volume":"5","author":"Motoyama","year":"2003","journal-title":"Breast Cancer Res."},{"key":"2023012508221182000_B47","doi-asserted-by":"crossref","first-page":"674","DOI":"10.4161\/cbt.5.6.2906","article-title":"Hedgehog signaling and response to cyclopamine differ in epithelial and stromal cells in benign breast and breast cancer","volume":"5","author":"Mukherjee","year":"2006","journal-title":"Cancer Biol. Ther."},{"key":"2023012508221182000_B48","author":"Naftel","year":"1985","journal-title":"Conservation of events"},{"key":"2023012508221182000_B49","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/S0304-3835(03)00276-3","article-title":"Transcriptional upregulation of interferon-induced protein kinase, PKR, in breast cancer","volume":"196","author":"Nussbaum","year":"2003","journal-title":"Cancer Lett."},{"key":"2023012508221182000_B50","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.1093\/jnci\/84.23.1825","article-title":"Can thymidine kinase levels in breast tumors predict disease recurrence?","volume":"84","author":"O'Neill","year":"1992","journal-title":"J. Natl Cancer Inst."},{"key":"2023012508221182000_B51","doi-asserted-by":"crossref","first-page":"2028","DOI":"10.1093\/bioinformatics\/btl344","article-title":"Pathway analysis using random forests classification and regression","volume":"22","author":"Pang","year":"2006","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B52","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1186\/1471-2105-9-87","article-title":"Building pathway clusters from Random Forests classification using class votes","volume":"9","author":"Pang","year":"2008","journal-title":"BMC Bioinformatics"},{"issue":"Suppl. 1","key":"2023012508221182000_B53","first-page":"S120","article-title":"Linking gene expression data with patient survival times using partial least squares","volume":"18","author":"Park","year":"2002","journal-title":"Stat. Med."},{"key":"2023012508221182000_B54","doi-asserted-by":"crossref","first-page":"1767","DOI":"10.1002\/sim.1769","article-title":"Gene expression profiling for prognosis using Cox regression","volume":"23","author":"Pawitan","year":"2004","journal-title":"Stat. Med."},{"key":"2023012508221182000_B55","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511543494.011","article-title":"Neural networks as statistical methods in survival analysis","volume-title":"Clinical Applications of Artificial Neural Networks.","author":"Ripley","year":"2001"},{"key":"2023012508221182000_B56","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1002\/sim.1655","article-title":"Non-linear survival analysis using neural networks","volume":"23","author":"Ripley","year":"2004","journal-title":"Stat. Med."},{"key":"2023012508221182000_B57","doi-asserted-by":"crossref","first-page":"1768","DOI":"10.1093\/bioinformatics\/btm232","article-title":"Assessment of survival prediction models based on microarray data","volume":"23","author":"Schumacher","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B58","doi-asserted-by":"crossref","first-page":"35","DOI":"10.2307\/2531894","article-title":"Regression trees for censored data","volume":"44","author":"Segal","year":"1988","journal-title":"Biometrics"},{"key":"2023012508221182000_B59","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1002\/ijc.11717","article-title":"Breakdown of the regulatory control of pyrimidine biosynthesis in human breast cancer cells","volume":"109","author":"Sigoillot","year":"2004","journal-title":"Int. J. Cancer"},{"key":"2023012508221182000_B60","first-page":"220","article-title":"On the asymptotic theory of permutation statistics","volume":"8","author":"Strasser","year":"1999","journal-title":"Math. Methods Stat."},{"key":"2023012508221182000_B61","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012508221182000_B62","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1093\/bioinformatics\/btm234","article-title":"Incorporating prior knowledge of predictors into penalized classifiers with multiple penalty terms","volume":"23","author":"Tai","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B63","doi-asserted-by":"crossref","first-page":"8643","DOI":"10.1158\/0008-5472.CAN-07-0982","article-title":"Transforming growth factor-beta can suppress tumorigenesis through effects on the putative cancer stem or early progenitor cell and committed progeny in a breast cancer xenograft model","volume":"67","author":"Tang","year":"2007","journal-title":"Cancer Res"},{"key":"2023012508221182000_B64","article-title":"An introduction to recursive partitioning using the RPART routine, Mayo Foundation","author":"Therneau","year":"1997","journal-title":"Technical Report."},{"key":"2023012508221182000_B65","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1016\/j.csda.2008.05.021","article-title":"Survival prediction using gene expression data: a review and comparison","volume":"53","author":"van Wieringen","year":"2009","journal-title":"Comput. Stat. Data Anal."},{"key":"2023012508221182000_B66","doi-asserted-by":"crossref","first-page":"R33","DOI":"10.1186\/bcr1681","article-title":"Low E2F1 transcript levels are a strong determinant of favorable breast cancer outcome","volume":"9","author":"Vuaroqueaux","year":"2007","journal-title":"Breast Cancer Res"},{"key":"2023012508221182000_B67","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1093\/bioinformatics\/btm129","article-title":"A Markov random field model for network-based analysis of genomic data","volume":"23","author":"Wei","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B68","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1677\/jme.0.0320595","article-title":"Ubiquitinated or sumoylated retinoic acid receptor alpha deter-mines its characteristic and interacting model with retinoid X receptor alpha in gastric and breast cancer cells","volume":"32","author":"Wu","year":"2004","journal-title":"J. Mol. Endocrinol."},{"key":"2023012508221182000_B69","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1093\/bioinformatics\/btp019","article-title":"Sparse linear discriminant analysis for simultaneous testing for the significance of a gene set\/pathway and gene selection","volume":"25","author":"Wu","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012508221182000_B70","doi-asserted-by":"crossref","first-page":"6286","DOI":"10.1158\/0008-5472.CAN-06-2205","article-title":"BRCA1 activates a G2-M cell cycle checkpoint following 6-thioguanine-induced DNA mismatch damage","volume":"67","author":"Yamane","year":"2007","journal-title":"Cancer Res."},{"key":"2023012508221182000_B71","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1038\/ng837","article-title":"BRCA1 regulates the G2\/M checkpoint by activating Chk1 kinase upon DNA damage","volume":"30","author":"Yarden","year":"2002","journal-title":"Nat. Genet."},{"key":"2023012508221182000_B72","doi-asserted-by":"crossref","first-page":"1686","DOI":"10.1074\/mcp.M400221-MCP200","article-title":"Proteomic study reveals that proteins involved in metabolic and detoxification pathways are highly expressed in HER-2\/neu-positive breast cancer","volume":"4","author":"Zhang","year":"2005","journal-title":"Mol. Cell Proteomics"},{"key":"2023012508221182000_B73","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1002\/ijc.23321","article-title":"Apoptosis of estrogen-receptor negative breast cancer and colon cancer cell lines by PTP alpha and src RNAi","volume":"222","author":"Zheng","year":"2008","journal-title":"Int. J. Cancer"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/2\/250\/48857907\/bioinformatics_26_2_250.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/2\/250\/48857907\/bioinformatics_26_2_250.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T08:23:05Z","timestamp":1674634985000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/26\/2\/250\/209807"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,11,18]]},"references-count":73,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2010,1,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btp640","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2010,1,15]]},"published":{"date-parts":[[2009,11,18]]}}}