{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T02:48:55Z","timestamp":1750992535766,"version":"3.37.3"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2017,1,19]],"date-time":"2017-01-19T00:00:00Z","timestamp":1484784000000},"content-version":"vor","delay-in-days":22,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01CA190766"],"award-info":[{"award-number":["R01CA190766"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201508110051"],"award-info":[{"award-number":["201508110051"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"crossref","award":["11526146"],"award-info":[{"award-number":["11526146"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology in Taiwan","doi-asserted-by":"crossref","award":["103-2917-I-002-020"],"award-info":[{"award-number":["103-2917-I-002-020"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100001006","name":"BCRF","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100001006","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Gene co-expression network analysis from transcriptomic studies can elucidate gene\u2013gene interactions and regulatory mechanisms. Differential co-expression analysis helps further detect alterations of regulatory activities in case\/control comparison. Co-expression networks estimated from single transcriptomic study is often unstable and not generalizable due to cohort bias and limited sample size. With the rapid accumulation of publicly available transcriptomic studies, co-expression analysis combining multiple transcriptomic studies can provide more accurate and robust results.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this paper, we propose a meta-analytic framework for detecting differentially co-expressed networks (MetaDCN). Differentially co-expressed seed modules are first detected by optimizing an energy function via simulated annealing. Basic modules sharing common pathways are merged into pathway-centric supermodules and a Cytoscape plug-in (MetaDCNExplorer) is developed to visualize and explore the findings. We applied MetaDCN to two breast cancer applications: ER+\/ER- comparison using five training and three testing studies, and ILC\/IDC comparison with two training and two testing studies. We identified 20 and 4 supermodules for ER+\/ER- and ILC\/IDC comparisons, respectively. Ranking atop are \u2018immune response pathway\u2019 and \u2018complement cascades pathway\u2019 for ER comparison, and \u2018extracellular matrix pathway\u2019 for ILC\/IDC comparison. Without the need for prior information, the results from MetaDCN confirm existing as well as discover novel disease mechanisms in a systems manner.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and Implementation<\/jats:title>\n                  <jats:p>R package \u2018MetaDCN\u2019 and Cytoscape App \u2018MetaDCNExplorer\u2019 are available at http:\/\/tsenglab.biostat.pitt.edu\/software.htm.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btw788","type":"journal-article","created":{"date-parts":[[2016,12,8]],"date-time":"2016-12-08T12:05:45Z","timestamp":1481198745000},"page":"1121-1129","source":"Crossref","is-referenced-by-count":21,"title":["MetaDCN: meta-analysis framework for differential co-expression network detection with an application in breast cancer"],"prefix":"10.1093","volume":"33","author":[{"given":"Li","family":"Zhu","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA"}]},{"given":"Ying","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA"}]},{"given":"Cho-Yi","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA"},{"name":"Genome and Systems Biology Degree Program, National Taiwan University, Taipei, Taiwan"}]},{"given":"Lin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA"}]},{"given":"Zhiguang","family":"Huo","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA"}]},{"given":"SungHwan","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA"}]},{"given":"Christos","family":"Sotiriou","sequence":"additional","affiliation":[{"name":"Breast Cancer Translational Research Laboratory, J. 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