{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T00:06:38Z","timestamp":1744157198865,"version":"3.37.3"},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2017,11,27]],"date-time":"2017-11-27T00:00:00Z","timestamp":1511740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000913","name":"James S. McDonnell Foundation","doi-asserted-by":"publisher","award":["220020394"],"award-info":[{"award-number":["220020394"]}],"id":[{"id":"10.13039\/100000913","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS-1547394"],"award-info":[{"award-number":["DMS-1547394"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Inferring the structure of gene regulatory networks from high-throughput datasets remains an important and unsolved problem. Current methods are hampered by problems such as noise, low sample size, and incomplete characterizations of regulatory dynamics, leading to networks with missing and anomalous links. Integration of prior network information (e.g. from pathway databases) has the potential to improve reconstructions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We developed a semi-supervised network reconstruction algorithm that enables the synthesis of information from partially known networks with time course gene expression data. We adapted partial least square-variable importance in projection (VIP) for time course data and used reference networks to simulate expression data from which null distributions of VIP scores are generated and used to estimate edge probabilities for input expression data. By using simulated dynamics to generate reference distributions, this approach incorporates previously known regulatory relationships and links the network to the dynamics to form a semi-supervised approach that discovers novel and anomalous connections. We applied this approach to data from a sleep deprivation study with KEGG pathways treated as prior networks, as well as to synthetic data from several DREAM challenges, and find that it is able to recover many of the true edges and identify errors in these networks, suggesting its ability to derive posterior networks that accurately reflect gene expression dynamics.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>R code is available at https:\/\/github.com\/pn51\/postPLSR.<\/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\/btx748","type":"journal-article","created":{"date-parts":[[2017,11,24]],"date-time":"2017-11-24T04:12:27Z","timestamp":1511496747000},"page":"1148-1156","source":"Crossref","is-referenced-by-count":7,"title":["Semi-supervised network inference using simulated gene expression dynamics"],"prefix":"10.1093","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8002-2979","authenticated-orcid":false,"given":"Phan","family":"Nguyen","sequence":"first","affiliation":[{"name":"Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA"}]},{"given":"Rosemary","family":"Braun","sequence":"additional","affiliation":[{"name":"Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA"},{"name":"Biostatistics Division, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA"}]}],"member":"286","published-online":{"date-parts":[[2017,11,27]]},"reference":[{"key":"2023012712572771800_btx748-B1","doi-asserted-by":"crossref","first-page":"2493","DOI":"10.1093\/bioinformatics\/bth283","article-title":"Analyzing time series gene expression data","volume":"20","author":"Bar-Joseph","year":"2004","journal-title":"Bioinformatics"},{"key":"2023012712572771800_btx748-B2","doi-asserted-by":"crossref","first-page":"R36","DOI":"10.1186\/gb-2006-7-5-r36","article-title":"The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo","volume":"7","author":"Bonneau","year":"2006","journal-title":"Genome Biol"},{"first-page":"711","year":"1999","author":"Butte","key":"2023012712572771800_btx748-B3"},{"key":"2023012712572771800_btx748-B4","first-page":"415","article-title":"Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements","volume":"5","author":"Butte","year":"2000","journal-title":"Pac. Symp. Biocomput"},{"key":"2023012712572771800_btx748-B5","doi-asserted-by":"crossref","first-page":"3841","DOI":"10.1091\/mbc.e03-11-0794","article-title":"Integrative analysis of cell cycle control in budding yeast","volume":"15","author":"Chen","year":"2004","journal-title":"Mol. Biol. Cell"},{"key":"2023012712572771800_btx748-B6","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.chemolab.2004.12.011","article-title":"Performance of some variable selection methods when multicollinearity is present","volume":"78","author":"Chong","year":"2005","journal-title":"Chemo. Intel. Lab. Syst"},{"key":"2023012712572771800_btx748-B7","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1039\/C5IB00065C","article-title":"The DIONESUS algorithm provides scalable and accurate reconstruction of dynamic phosphoproteomic networks to reveal new drug targets","volume":"7","author":"Ciaccio","year":"2015","journal-title":"Integr. Biol"},{"key":"2023012712572771800_btx748-B8","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1038\/nature06830","article-title":"Hierarchical structure and the prediction of missing links in networks","volume":"453","author":"Clauset","year":"2008","journal-title":"Nature"},{"key":"2023012712572771800_btx748-B9","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1089\/10665270252833208","article-title":"Modeling and simulation of genetic regulatory systems: a literature review","volume":"9","author":"de Jong","year":"2002","journal-title":"J. Comput. Biol"},{"key":"2023012712572771800_btx748-B10","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s101420000035","article-title":"Dynamic models of gene expression and classification","volume":"1","author":"Dewey","year":"2001","journal-title":"Funct. Integr. Genomics"},{"key":"2023012712572771800_btx748-B11","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1038\/35002125","article-title":"A synthetic oscillatory network of transcriptional regulators","volume":"403","author":"Elowitz","year":"1999","journal-title":"Nature"},{"key":"2023012712572771800_btx748-B12","doi-asserted-by":"crossref","first-page":"e8","DOI":"10.1371\/journal.pbio.0050008","article-title":"Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles","volume":"5","author":"Faith","year":"2007","journal-title":"PLoS Biol"},{"key":"2023012712572771800_btx748-B13","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1126\/science.1094068","article-title":"Inferring cellular networks using probabilistic graphical models","volume":"303","author":"Friedman","year":"2004","journal-title":"Science"},{"key":"2023012712572771800_btx748-B14","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1126\/science.1081900","article-title":"Inferring genetic networks and identifying compound mode of action via expression profiling","volume":"301","author":"Gardner","year":"2001","journal-title":"Science"},{"key":"2023012712572771800_btx748-B15","doi-asserted-by":"crossref","first-page":"22073","DOI":"10.1073\/pnas.0908366106","article-title":"Missing and spurious interactions and the reconstruction of complex networks","volume":"106","author":"Guimer\u00e0","year":"2009","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023012712572771800_btx748-B16","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1186\/s12859-016-1398-6","article-title":"Gene regulatory network inference using pls-based methods","volume":"17","author":"Guo","year":"2016","journal-title":"BMC Bioinformatics"},{"key":"2023012712572771800_btx748-B17","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1186\/1752-0509-6-145","article-title":"TIGRESS: Trustful Inference of Gene REgulation using Stability Selection","volume":"6","author":"Haury","year":"2012","journal-title":"BMC Syst. Biol"},{"key":"2023012712572771800_btx748-B18","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1002\/cem.1180020306","article-title":"PLS regression methods","volume":"2","author":"H\u00f6skuldsson","year":"1988","journal-title":"J. Chem"},{"key":"2023012712572771800_btx748-B19","doi-asserted-by":"crossref","first-page":"e12776","DOI":"10.1371\/journal.pone.0012776","article-title":"Inferring regulatory networks from expression data using tree-based methods","volume":"5","author":"Huynh-Thu","year":"2010","journal-title":"PLoS One"},{"key":"2023012712572771800_btx748-B20","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.coisb.2017.04.004","article-title":"Computational methods to dissect gene regulatory networks in cancer","volume":"2","author":"Iyer","year":"2017","journal-title":"Curr. Opin. Syst. Biol"},{"key":"2023012712572771800_btx748-B21","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1093\/nar\/28.1.27","article-title":"KEGG: Kyoto encyclopedia of genes and genomes","volume":"28","author":"Kanehisa","year":"2000","journal-title":"Nucleic Acids Res"},{"key":"2023012712572771800_btx748-B22","doi-asserted-by":"crossref","first-page":"D199","DOI":"10.1093\/nar\/gkt1076","article-title":"Data, information, knowledge and principle: back to metabolism in kegg","volume":"42","author":"Kanehisa","year":"2014","journal-title":"Nucleic Acids Res"},{"key":"2023012712572771800_btx748-B23","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1038\/nrm2503","article-title":"Modelling and analysis of gene regulatory networks","volume":"9","author":"Karlebach","year":"2008","journal-title":"Nat. Rev. Mol. Cell Biol"},{"key":"2023012712572771800_btx748-B24","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1038\/224177a0","article-title":"Homeostasis and differentiation in random genetic control networks","volume":"224","author":"Kauffman","year":"1969","journal-title":"Nature"},{"key":"2023012712572771800_btx748-B25","doi-asserted-by":"crossref","first-page":"1150","DOI":"10.1016\/j.physa.2010.11.027","article-title":"Link prediction in complex networks: a survey","volume":"390","author":"L\u00fc","year":"2011","journal-title":"Phys. A Stat. Mech Appl"},{"key":"2023012712572771800_btx748-B26","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1101\/gr.097378.109","article-title":"Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression","volume":"21","author":"MacNeil","year":"2011","journal-title":"Genome Res"},{"key":"2023012712572771800_btx748-B27","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1089\/cmb.2008.09TT","article-title":"Generating realistic in silico gene networks for performance assessment of reverse engineering methods","volume":"16","author":"Marbach","year":"2009","journal-title":"J. Comput. Biol"},{"key":"2023012712572771800_btx748-B28","doi-asserted-by":"crossref","first-page":"6286","DOI":"10.1073\/pnas.0913357107","article-title":"Revealing strengths and weaknesses of methods for gene network inference","volume":"107","author":"Marbach","year":"2010","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023012712572771800_btx748-B29","doi-asserted-by":"crossref","first-page":"S7","DOI":"10.1186\/1471-2105-7-S1-S7","article-title":"ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context","volume":"7","author":"Margolin","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2023012712572771800_btx748-B30","doi-asserted-by":"crossref","first-page":"E1132","DOI":"10.1073\/pnas.1217154110","article-title":"Effects of insufficient sleep on circadian rhythmicity and expression amplitude of the human blood transcriptome","volume":"110","author":"M\u00f6ller-Levet","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023012712572771800_btx748-B31","doi-asserted-by":"crossref","first-page":"ii138","DOI":"10.1093\/bioinformatics\/btg1071","article-title":"Gene networks inference using dynamic Bayesian networks","volume":"19","author":"Perrin","year":"2003","journal-title":"Bioinformatics"},{"key":"2023012712572771800_btx748-B32","doi-asserted-by":"crossref","first-page":"i197","DOI":"10.1093\/bioinformatics\/btv268","article-title":"Integrative random forest for gene regulatory network inference","volume":"31","author":"Petralia","year":"2015","journal-title":"Bioinformatics"},{"key":"2023012712572771800_btx748-B33","doi-asserted-by":"crossref","first-page":"2836","DOI":"10.1093\/bioinformatics\/btv215","article-title":"Addressing false discoveries in network inference","volume":"31","author":"Petri","year":"2015","journal-title":"Bioinformatics"},{"key":"2023012712572771800_btx748-B34","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1093\/bioinformatics\/btm640","article-title":"Reconstruction of genetic association networks from microarray data: a partial least squares approach","volume":"24","author":"Pihur","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012712572771800_btx748-B35","doi-asserted-by":"crossref","first-page":"e9202","DOI":"10.1371\/journal.pone.0009202","article-title":"Towards a rigorous assessment of systems biology models: the DREAM3 challenges","volume":"5","author":"Prill","year":"2010","journal-title":"PLoS One"},{"key":"2023012712572771800_btx748-B36","doi-asserted-by":"crossref","first-page":"e0152648","DOI":"10.1371\/journal.pone.0152648","article-title":"DTW-MIC coexpression networks from time-course data","volume":"11","author":"Riccadonna","year":"2016","journal-title":"PLoS One"},{"key":"2023012712572771800_btx748-B37","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1093\/bioinformatics\/bti064","article-title":"Reconstructing biological networks using conditional correlation analysis","volume":"21","author":"Rice","year":"2005","journal-title":"Bioinformatics"},{"key":"2023012712572771800_btx748-B38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-10-253","article-title":"A fast and efficient gene-network reconstruction method from multiple over-expression experiments","volume":"10","author":"Stoki\u0107","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2023012712572771800_btx748-B39","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1111\/j.1749-6632.2009.04497.x","article-title":"Lessons from the DREAM2 challenges","volume":"1158","author":"Stolovitzky","year":"2009","journal-title":"Ann. N. Y. Acad. Sci"},{"key":"2023012712572771800_btx748-B40","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1049\/iet-syb.2012.0063","article-title":"Gene regulatory network discovery using pairwise Granger causality","volume":"7","author":"Tam","year":"2013","journal-title":"IET Syst. Biol"},{"key":"2023012712572771800_btx748-B41","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1146\/annurev-cellbio-100913-012908","article-title":"Comparative analysis of gene regulatory networks: From network reconstruction to evolution","volume":"31","author":"Thompson","year":"2015","journal-title":"Annu. Rev. Cell Dev. Biol"},{"key":"2023012712572771800_btx748-B42","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/0-387-26288-1_14","volume-title":"Computational and Statistical Approaches to Genomics","author":"van Someren","year":"2006"},{"key":"2023012712572771800_btx748-B43","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.jtbi.2014.03.040","article-title":"Review on statistical methods for gene network reconstruction using expression data","volume":"362","author":"Wang","year":"2014","journal-title":"J. Theor. Biol"},{"key":"2023012712572771800_btx748-B44","first-page":"112","article-title":"Modeling regulatory networks with weight matrices","volume":"4","author":"Weaver","year":"1999","journal-title":"Pac. Symp. Biocomput"},{"key":"2023012712572771800_btx748-B45","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0169-7439(01)00155-1","article-title":"PLS-regression: a basic tool of chemometrics","volume":"58","author":"Wold","year":"2001","journal-title":"Chem. Intell. Lab. Syst"},{"key":"2023012712572771800_btx748-B46","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1186\/1471-2105-11-154","article-title":"TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach","volume":"11","author":"Zoppoli","year":"2010","journal-title":"BMC Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/34\/7\/1148\/48914573\/bioinformatics_34_7_1148.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/34\/7\/1148\/48914573\/bioinformatics_34_7_1148.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T13:45:58Z","timestamp":1674827158000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/34\/7\/1148\/4665418"}},"subtitle":[],"editor":[{"given":"Inanc","family":"Birol","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2017,11,27]]},"references-count":46,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2018,4,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btx748","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2018,4,1]]},"published":{"date-parts":[[2017,11,27]]}}}