{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:16:57Z","timestamp":1772173017364,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1009767","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T00:00:00Z","timestamp":1663286400000}}],"reference-count":77,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T00:00:00Z","timestamp":1662422400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","award":["Synergy Grant 609883"],"award-info":[{"award-number":["Synergy Grant 609883"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012390","name":"SystemsX.ch","doi-asserted-by":"publisher","award":["Research, Technology and Development (RTD) Grant 2013\/150"],"award-info":[{"award-number":["Research, Technology and Development (RTD) Grant 2013\/150"]}],"id":[{"id":"10.13039\/501100012390","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Comprehensive molecular characterization of cancer subtypes is essential for predicting clinical outcomes and searching for personalized treatments. We present bnClustOmics, a statistical model and computational tool for multi-omics unsupervised clustering, which serves a dual purpose: Clustering patient samples based on a Bayesian network mixture model and learning the networks of omics variables representing these clusters. The discovered networks encode interactions among all omics variables and provide a molecular characterization of each patient subgroup. We conducted simulation studies that demonstrated the advantages of our approach compared to other clustering methods in the case where the generative model is a mixture of Bayesian networks. We applied bnClustOmics to a hepatocellular carcinoma (HCC) dataset comprising genome (mutation and copy number), transcriptome, proteome, and phosphoproteome data. We identified three main HCC subtypes together with molecular characteristics, some of which are associated with survival even when adjusting for the clinical stage. Cluster-specific networks shed light on the links between genotypes and molecular phenotypes of samples within their respective clusters and suggest targets for personalized treatments.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1009767","type":"journal-article","created":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T13:49:05Z","timestamp":1662472145000},"page":"e1009767","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":11,"title":["Multi-omics subtyping of hepatocellular carcinoma patients using a Bayesian network mixture model"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4514-0739","authenticated-orcid":true,"given":"Polina","family":"Suter","sequence":"first","affiliation":[]},{"given":"Eva","family":"Dazert","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5357-2705","authenticated-orcid":true,"given":"Jack","family":"Kuipers","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6100-0026","authenticated-orcid":true,"given":"Charlotte K. Y.","family":"Ng","sequence":"additional","affiliation":[]},{"given":"Tuyana","family":"Boldanova","sequence":"additional","affiliation":[]},{"given":"Michael N.","family":"Hall","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7523-4894","authenticated-orcid":true,"given":"Markus H.","family":"Heim","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0573-6119","authenticated-orcid":true,"given":"Niko","family":"Beerenwinkel","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2022,9,6]]},"reference":[{"issue":"12","key":"pcbi.1009767.ref001","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1002\/cac2.12115","article-title":"Molecular subtyping of hepatocellular carcinoma: A step toward precision medicine","volume":"40","author":"Y Wu","year":"2020","journal-title":"Cancer Communications"},{"issue":"S4","key":"pcbi.1009767.ref002","article-title":"Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus","volume":"10","author":"M Cai","year":"2017","journal-title":"BMC Medical Genomics"},{"issue":"8","key":"pcbi.1009767.ref003","doi-asserted-by":"crossref","first-page":"1814","DOI":"10.1093\/annonc\/mdy224","article-title":"Comprehensive molecular classification of localized prostate adenocarcinoma reveals a tumour subtype predictive of non-aggressive disease","volume":"29","author":"A Kamoun","year":"2018","journal-title":"Annals of Oncology"},{"issue":"2","key":"pcbi.1009767.ref004","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1038\/s41422-020-0375-9","article-title":"Molecular subtyping and genomic profiling expand precision medicine in refractory metastatic triple-negative breast cancer: the FUTURE trial","volume":"31","author":"YZ Jiang","year":"2020","journal-title":"Cell Research"},{"issue":"7","key":"pcbi.1009767.ref005","first-page":"1602","article-title":"Gene expression-based classification of malignant gliomas correlates better with survival than histological classification","volume":"63","author":"CL Nutt","year":"2003","journal-title":"Cancer Res"},{"issue":"6","key":"pcbi.1009767.ref006","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1093\/bib\/bbz138","article-title":"Clustering and variable selection evaluation of 13 unsupervised methods for multi-omics data integration","volume":"21","author":"M Pierre-Jean","year":"2019","journal-title":"Briefings in Bioinformatics"},{"issue":"20","key":"pcbi.1009767.ref007","doi-asserted-by":"crossref","first-page":"10546","DOI":"10.1093\/nar\/gky889","article-title":"Multi-omic and multi-view clustering algorithms: review and cancer benchmark","volume":"46","author":"N Rappoport","year":"2018","journal-title":"Nucleic Acids Research"},{"issue":"4","key":"pcbi.1009767.ref008","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1093\/bib\/bbx167","article-title":"Multi-omics integration\u2014a comparison of unsupervised clustering methodologies","volume":"20","author":"G Tini","year":"2017","journal-title":"Briefings in Bioinformatics"},{"issue":"1","key":"pcbi.1009767.ref009","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1007\/s40484-016-0063-4","article-title":"Integrative clustering methods of multi-omics data for molecule-based cancer classifications","volume":"4","author":"D Wang","year":"2016","journal-title":"Quantitative Biology"},{"issue":"14","key":"pcbi.1009767.ref010","doi-asserted-by":"crossref","first-page":"2441","DOI":"10.1093\/bioinformatics\/bty148","article-title":"Network-based integration of multi-omics data for prioritizing cancer genes","volume":"34","author":"C Dimitrakopoulos","year":"2018","journal-title":"Bioinformatics"},{"issue":"5","key":"pcbi.1009767.ref011","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1016\/j.cels.2019.04.005","article-title":"Simultaneous Integration of Multi-omics Data Improves the Identification of Cancer Driver Modules","volume":"8","author":"D Silverbush","year":"2019","journal-title":"Cell Systems"},{"issue":"1","key":"pcbi.1009767.ref012","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s13167-018-0128-8","article-title":"The crucial role of multiomic approach in cancer research and clinically relevant outcomes","volume":"9","author":"M Lu","year":"2018","journal-title":"EPMA Journal"},{"issue":"2","key":"pcbi.1009767.ref013","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s00109-020-01874-2","article-title":"Clinical implications of intratumor heterogeneity: challenges and opportunities","volume":"98","author":"SR Cajal","year":"2020","journal-title":"Journal of Molecular Medicine"},{"issue":"1","key":"pcbi.1009767.ref014","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-018-06867-x","article-title":"Mutational interactions define novel cancer subgroups","volume":"9","author":"J Kuipers","year":"2018","journal-title":"Nature Communications"},{"issue":"11","key":"pcbi.1009767.ref015","doi-asserted-by":"crossref","first-page":"1108","DOI":"10.1038\/nmeth.2651","article-title":"Network-based stratification of tumor mutations","volume":"10","author":"M Hofree","year":"2013","journal-title":"Nature Methods"},{"issue":"16","key":"pcbi.1009767.ref016","doi-asserted-by":"crossref","first-page":"2398","DOI":"10.1093\/bioinformatics\/btaa1076","article-title":"BiCoN: network-constrained biclustering of patients and omics data","volume":"37","author":"O Lazareva","year":"2020","journal-title":"Bioinformatics"},{"issue":"1","key":"pcbi.1009767.ref017","article-title":"iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery","volume":"5","author":"HWL Koh","year":"2019","journal-title":"npj Systems Biology and Applications"},{"issue":"12","key":"pcbi.1009767.ref018","doi-asserted-by":"crossref","first-page":"i237","DOI":"10.1093\/bioinformatics\/btq182","article-title":"Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM","volume":"26","author":"CJ Vaske","year":"2010","journal-title":"Bioinformatics"},{"key":"pcbi.1009767.ref019","first-page":"49","volume-title":"Gene Regulatory Networks","author":"M Grzegorczyk","year":"2018"},{"issue":"S9","key":"pcbi.1009767.ref020","doi-asserted-by":"crossref","DOI":"10.1186\/s12864-017-4228-y","article-title":"An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection","volume":"18","author":"L Xing","year":"2017","journal-title":"BMC Genomics"},{"issue":"1","key":"pcbi.1009767.ref021","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-020-17387-y","article-title":"Multi-layered proteomic analyses decode compositional and functional effects of cancer mutations on kinase complexes","volume":"11","author":"M Mehnert","year":"2020","journal-title":"Nature Communications"},{"issue":"8","key":"pcbi.1009767.ref022","doi-asserted-by":"crossref","first-page":"e1009224","DOI":"10.1371\/journal.pcbi.1009224","article-title":"Evaluation and comparison of multi-omics data integration methods for cancer subtyping","volume":"17","author":"R Duan","year":"2021","journal-title":"PLoS Computational Biology"},{"issue":"6","key":"pcbi.1009767.ref023","doi-asserted-by":"crossref","first-page":"1920","DOI":"10.1093\/bib\/bbz121","article-title":"A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping","volume":"21","author":"A Sathyanarayanan","year":"2019","journal-title":"Briefings in Bioinformatics"},{"issue":"11","key":"pcbi.1009767.ref024","doi-asserted-by":"crossref","first-page":"4245","DOI":"10.1073\/pnas.1208949110","article-title":"Pattern discovery and cancer gene identification in integrated cancer genomic data","volume":"110","author":"Q Mo","year":"2013","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"1","key":"pcbi.1009767.ref025","doi-asserted-by":"crossref","DOI":"10.1038\/s41467-018-06921-8","article-title":"Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival","volume":"9","author":"D Ramazzotti","year":"2018","journal-title":"Nature Communications"},{"issue":"6","key":"pcbi.1009767.ref026","doi-asserted-by":"crossref","DOI":"10.15252\/msb.20178124","article-title":"Multi-Omics Factor Analysis\u2014a framework for unsupervised integration of multi-omics data sets","volume":"14","author":"R Argelaguet","year":"2018","journal-title":"Molecular Systems Biology"},{"key":"pcbi.1009767.ref027","article-title":"Proteogenomic characterization of hepatocellular carcinoma","author":"CKY Ng","year":"2021","journal-title":"bioRxiv"},{"issue":"3","key":"pcbi.1009767.ref028","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1038\/s41575-019-0229-4","article-title":"Tumour evolution in hepatocellular carcinoma","volume":"17","author":"AJ Craig","year":"2019","journal-title":"Nature Reviews Gastroenterology & Hepatology"},{"issue":"D1","key":"pcbi.1009767.ref029","doi-asserted-by":"crossref","first-page":"D605","DOI":"10.1093\/nar\/gkaa1074","article-title":"The STRING database in 2021: customizable protein\u2013protein networks, and functional characterization of user-uploaded gene\/measurement sets","volume":"49","author":"D Szklarczyk","year":"2020","journal-title":"Nucleic Acids Research"},{"issue":"9","key":"pcbi.1009767.ref030","doi-asserted-by":"crossref","first-page":"e2003243","DOI":"10.1371\/journal.pbio.2003243","article-title":"60 years ago, Francis Crick changed the logic of biology","volume":"15","author":"M Cobb","year":"2017","journal-title":"PLoS Biology"},{"key":"pcbi.1009767.ref031","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10618600.2021.2020127","article-title":"Efficient Sampling and Structure Learning of Bayesian Networks","author":"J Kuipers","year":"2022","journal-title":"Journal of Computational and Graphical Statistics"},{"key":"pcbi.1009767.ref032","doi-asserted-by":"crossref","unstructured":"Suter P, Kuipers J, Moffa G, Beerenwinkel N. Bayesian structure learning and sampling of Bayesian networks with the R package BiDAG. arXiv:210500488. 2021;.","DOI":"10.1080\/10618600.2021.2020127"},{"key":"pcbi.1009767.ref033","unstructured":"R Core Team. R: A Language and Environment for Statistical Computing; 2013. Available from: http:\/\/www.R-project.org\/."},{"issue":"1","key":"pcbi.1009767.ref034","doi-asserted-by":"crossref","first-page":"289","DOI":"10.32614\/RJ-2016-021","article-title":"mclust 5: clustering, classification and density estimation using Gaussian finite mixture models","volume":"8","author":"L Scrucca","year":"2016","journal-title":"The R Journal"},{"issue":"1","key":"pcbi.1009767.ref035","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/BF01908075","article-title":"Comparing partitions","volume":"2","author":"L Hubert","year":"1985","journal-title":"Journal of Classification"},{"issue":"D1","key":"pcbi.1009767.ref036","doi-asserted-by":"crossref","first-page":"D607","DOI":"10.1093\/nar\/gky1131","article-title":"STRING v11: protein\u2013protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets","volume":"47","author":"D Szklarczyk","year":"2018","journal-title":"Nucleic Acids Research"},{"issue":"1","key":"pcbi.1009767.ref037","first-page":"2","article-title":"Frequently mutated genes\/pathways and genomic instability as prevention targets in liver cancer","volume":"38","author":"CV Rao","year":"2016","journal-title":"Carcinogenesis"},{"issue":"7","key":"pcbi.1009767.ref038","doi-asserted-by":"crossref","first-page":"e100854","DOI":"10.1371\/journal.pone.0100854","article-title":"Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma","volume":"9","author":"Y Zhang","year":"2014","journal-title":"PLoS ONE"},{"issue":"7","key":"pcbi.1009767.ref039","doi-asserted-by":"crossref","first-page":"2462","DOI":"10.1002\/cam4.2903","article-title":"Integrative analysis of highly mutated genes in hepatitis B virus-related hepatic carcinoma","volume":"9","author":"F Kong","year":"2020","journal-title":"Cancer Medicine"},{"issue":"12","key":"pcbi.1009767.ref040","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1038\/nmeth.4077","article-title":"OmniPath: guidelines and gateway for literature-curated signaling pathway resources","volume":"13","author":"D T\u00fcrei","year":"2016","journal-title":"Nature Methods"},{"issue":"50","key":"pcbi.1009767.ref041","doi-asserted-by":"crossref","first-page":"E11874","DOI":"10.1073\/pnas.1807305115","article-title":"Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes","volume":"115","author":"G Bidkhori","year":"2018","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1009767.ref042","doi-asserted-by":"crossref","DOI":"10.3389\/fgene.2020.00654","article-title":"Gene Set Analysis: Challenges, Opportunities, and Future Research","volume":"11","author":"F Maleki","year":"2020","journal-title":"Frontiers in Genetics"},{"issue":"1","key":"pcbi.1009767.ref043","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.ccell.2017.12.011","article-title":"Arid1a Has Context-Dependent Oncogenic and Tumor Suppressor Functions in Liver Cancer","volume":"33","author":"X Sun","year":"2018","journal-title":"Cancer Cell"},{"issue":"1","key":"pcbi.1009767.ref044","doi-asserted-by":"crossref","DOI":"10.1186\/s13027-020-00297-5","article-title":"Investigation of CTNNB1 gene mutations and expression in hepatocellular carcinoma and cirrhosis in association with hepatitis B virus infection","volume":"15","author":"D Javanmard","year":"2020","journal-title":"Infectious Agents and Cancer"},{"issue":"18","key":"pcbi.1009767.ref045","doi-asserted-by":"crossref","first-page":"4997","DOI":"10.1158\/1078-0432.CCR-11-2322","article-title":"Wnt-Pathway Activation in Two Molecular Classes of Hepatocellular Carcinoma and Experimental Modulation by Sorafenib","volume":"18","author":"A Lachenmayer","year":"2012","journal-title":"Clinical Cancer Research"},{"issue":"8","key":"pcbi.1009767.ref046","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1158\/2159-8290.CD-19-0074","article-title":"\u03b2-Catenin Activation Promotes Immune Escape and Resistance to Anti\u2013PD-1 Therapy in Hepatocellular Carcinoma","volume":"9","author":"MR de Galarreta","year":"2019","journal-title":"Cancer Discovery"},{"issue":"7605","key":"pcbi.1009767.ref047","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/nature18003","article-title":"Proteogenomics connects somatic mutations to signalling in breast cancer","volume":"534","author":"P Mertins","year":"2016","journal-title":"Nature"},{"issue":"1","key":"pcbi.1009767.ref048","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3892\/ol.2015.3892","article-title":"Correlation between the expression of hTERT gene and the clinicopathological characteristics of hepatocellular carcinoma","volume":"11","author":"X Zhou","year":"2015","journal-title":"Oncology Letters"},{"issue":"20","key":"pcbi.1009767.ref049","doi-asserted-by":"crossref","first-page":"17873","DOI":"10.18632\/oncotarget.4286","article-title":"RB1 dual role in proliferation and apoptosis: Cell fate control and implications for cancer therapy","volume":"6","author":"P Indovina","year":"2015","journal-title":"Oncotarget"},{"issue":"D1","key":"pcbi.1009767.ref050","doi-asserted-by":"crossref","first-page":"D512","DOI":"10.1093\/nar\/gku1267","article-title":"PhosphoSitePlus, 2014: mutations, PTMs and recalibrations","volume":"43","author":"PV Hornbeck","year":"2014","journal-title":"Nucleic Acids Research"},{"issue":"4","key":"pcbi.1009767.ref051","doi-asserted-by":"crossref","first-page":"1094","DOI":"10.1158\/1078-0432.CCR-09-0787","article-title":"Targeting the RB-pathway in Cancer Therapy","volume":"16","author":"ES Knudsen","year":"2010","journal-title":"Clinical Cancer Research"},{"issue":"15_suppl","key":"pcbi.1009767.ref052","doi-asserted-by":"crossref","first-page":"10559","DOI":"10.1200\/jco.2011.29.15_suppl.10559","article-title":"The prognostic value of the downregulation of leukocyte cell-derived chemotaxin 2 gene of hepatocellular carcinoma","volume":"29","author":"C Yang","year":"2011","journal-title":"Journal of Clinical Oncology"},{"issue":"16","key":"pcbi.1009767.ref053","doi-asserted-by":"crossref","first-page":"4861","DOI":"10.1158\/0008-5472.CAN-16-0481","article-title":"Reduced Expression of Histone Methyltransferases KMT2C and KMT2D Correlates with Improved Outcome in Pancreatic Ductal Adenocarcinoma","volume":"76","author":"JBN Dawkins","year":"2016","journal-title":"Cancer Research"},{"issue":"11","key":"pcbi.1009767.ref054","doi-asserted-by":"crossref","first-page":"2144","DOI":"10.18632\/oncotarget.1555","article-title":"KMT2D maintains neoplastic cell proliferation and global histone H3 lysine 4 monomethylation","volume":"4","author":"C Guo","year":"2013","journal-title":"Oncotarget"},{"issue":"2","key":"pcbi.1009767.ref055","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.ygeno.2013.04.001","article-title":"Mutations in TP53, CTNNB1 and PIK3CA genes in hepatocellular carcinoma associated with hepatitis B and hepatitis C virus infections","volume":"102","author":"ML Tornesello","year":"2013","journal-title":"Genomics"},{"issue":"1","key":"pcbi.1009767.ref056","doi-asserted-by":"crossref","DOI":"10.1186\/s12907-016-0029-5","article-title":"Liver cancer with concomitant TP53 and CTNNB1 mutations: a case report","volume":"16","author":"J Friemel","year":"2016","journal-title":"BMC Clinical Pathology"},{"key":"pcbi.1009767.ref057","article-title":"Morphological heterogeneity in beta-catenin mutated hepatocellular carcinomas: implications for tumor molecular classification","author":"M Torbenson","year":"2021","journal-title":"Human Pathology"},{"issue":"6","key":"pcbi.1009767.ref058","doi-asserted-by":"crossref","first-page":"e88","DOI":"10.1371\/journal.pgen.0020088","article-title":"Why Do Hubs Tend to Be Essential in Protein Networks?","volume":"2","author":"X He","year":"2006","journal-title":"PLoS Genetics"},{"issue":"9","key":"pcbi.1009767.ref059","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1038\/nrg2450","article-title":"Why do we need hubs?","volume":"9","author":"P Goymer","year":"2008","journal-title":"Nature Reviews Genetics"},{"issue":"36","key":"pcbi.1009767.ref060","doi-asserted-by":"crossref","first-page":"4152","DOI":"10.3748\/wjg.v24.i36.4152","article-title":"Ten years of sorafenib in hepatocellular carcinoma: Are there any predictive and\/or prognostic markers?","volume":"24","author":"G Marisi","year":"2018","journal-title":"World Journal of Gastroenterology"},{"issue":"6","key":"pcbi.1009767.ref061","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1111\/j.1442-2050.2007.00799.x","article-title":"Sorafenib inhibits MAPK-mediated proliferation in a Barrett\u2019s esophageal adenocarcinoma cell line","volume":"21","author":"RN Keswani","year":"2008","journal-title":"Diseases of the Esophagus"},{"issue":"2","key":"pcbi.1009767.ref062","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1016\/j.jss.2011.10.045","article-title":"PKI-587 and Sorafenib Targeting PI3K\/AKT\/mTOR and Ras\/Raf\/MAPK Pathways Synergistically Inhibit HCC Cell Proliferation","volume":"176","author":"R Gedaly","year":"2012","journal-title":"Journal of Surgical Research"},{"issue":"21","key":"pcbi.1009767.ref063","doi-asserted-by":"crossref","first-page":"2628","DOI":"10.4161\/cc.6.21.4930","article-title":"Canonical and Alternative MAPK Signaling","volume":"6","author":"G Pimienta","year":"2007","journal-title":"Cell Cycle"},{"issue":"12","key":"pcbi.1009767.ref064","doi-asserted-by":"crossref","first-page":"2534","DOI":"10.1016\/j.cellsig.2015.09.017","article-title":"Distinct biological activity of threonine monophosphorylated MAPK isoforms during the stress response in fission yeast","volume":"27","author":"B V\u00e1zquez","year":"2015","journal-title":"Cellular Signalling"},{"issue":"6","key":"pcbi.1009767.ref065","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1097\/FPC.0000000000000279","article-title":"PharmGKB summary","volume":"27","author":"L Gong","year":"2017","journal-title":"Pharmacogenetics and Genomics"},{"issue":"3","key":"pcbi.1009767.ref066","doi-asserted-by":"crossref","first-page":"82","DOI":"10.3390\/cancers10030082","article-title":"The Roles of Protein Tyrosine Phosphatases in Hepatocellular Carcinoma","volume":"10","author":"Y Huang","year":"2018","journal-title":"Cancers"},{"issue":"7","key":"pcbi.1009767.ref067","doi-asserted-by":"crossref","first-page":"1834","DOI":"10.1073\/pnas.0304242101","article-title":"The role of protein tyrosine phosphatase 1B in Ras signaling","volume":"101","author":"N Dub\u00e9","year":"2004","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1009767.ref068","unstructured":"Protein tyrosine phosphatases non-receptor type (PTPN): protein tyrosine phosphatase non-receptor type 1.;. http:\/\/www.guidetopharmacology.org\/GRAC\/ObjectDisplayForward?objectId=2976."},{"issue":"1","key":"pcbi.1009767.ref069","doi-asserted-by":"crossref","first-page":"322","DOI":"10.3892\/ijo.2014.2419","article-title":"Effect of the anti-diabetic drug metformin in hepatocellular carcinoma in vitro and in vivo","volume":"45","author":"H Miyoshi","year":"2014","journal-title":"International Journal of Oncology"},{"key":"pcbi.1009767.ref070","doi-asserted-by":"crossref","DOI":"10.3389\/fgene.2018.00002","article-title":"Genomic Analysis Revealed New Oncogenic Signatures in TP53-Mutant Hepatocellular Carcinoma","volume":"9","author":"V Kancherla","year":"2018","journal-title":"Frontiers in Genetics"},{"issue":"7","key":"pcbi.1009767.ref071","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1038\/ng.2291","article-title":"Whole-genome sequencing of liver cancers identifies etiological influences on mutation patterns and recurrent mutations in chromatin regulators","volume":"44","author":"A Fujimoto","year":"2012","journal-title":"Nature Genetics"},{"issue":"5","key":"pcbi.1009767.ref072","doi-asserted-by":"crossref","DOI":"10.1214\/aos\/1035844981","article-title":"Parameter priors for directed acyclic graphical models and the characterization of several probability distributions","volume":"30","author":"D Geiger","year":"2002","journal-title":"The Annals of Statistics"},{"issue":"4","key":"pcbi.1009767.ref073","doi-asserted-by":"crossref","DOI":"10.1214\/14-AOS1217","article-title":"Addendum on the scoring of Gaussian directed acyclic graphical models","volume":"42","author":"J Kuipers","year":"2014","journal-title":"The Annals of Statistics"},{"issue":"2","key":"pcbi.1009767.ref074","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1039\/C5MB00663E","article-title":"ReactomePA: an R\/Bioconductor package for reactome pathway analysis and visualization","volume":"12","author":"G Yu","year":"2016","journal-title":"Molecular BioSystems"},{"issue":"1","key":"pcbi.1009767.ref075","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","article-title":"edgeR: a Bioconductor package for differential expression analysis of digital gene expression data","volume":"26","author":"MD Robinson","year":"2009","journal-title":"Bioinformatics"},{"issue":"7","key":"pcbi.1009767.ref076","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"ME Ritchie","year":"2015","journal-title":"Nucleic Acids Research"},{"key":"pcbi.1009767.ref077","first-page":"1695","article-title":"The igraph software package for complex network research","author":"G Csardi","year":"2006","journal-title":"InterJournal"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1009767","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T00:00:00Z","timestamp":1663286400000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1009767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T13:59:31Z","timestamp":1663336771000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1009767"}},"subtitle":[],"editor":[{"given":"Carl","family":"Herrmann","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,9,6]]},"references-count":77,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,9,6]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1009767","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.12.16.473083","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,6]]}}}