{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T13:09:17Z","timestamp":1769605757278,"version":"3.49.0"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T00:00:00Z","timestamp":1738713600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T00:00:00Z","timestamp":1738713600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Kansas Institute of Precision Medicine","award":["NIH 5P20GM130423"],"award-info":[{"award-number":["NIH 5P20GM130423"]}]},{"name":"Kansas Institute of Precision Medicine","award":["NIH 5P20GM130423"],"award-info":[{"award-number":["NIH 5P20GM130423"]}]},{"name":"NCI Cancer Center Support Grant","award":["P30CA168524"],"award-info":[{"award-number":["P30CA168524"]}]},{"name":"NCI Cancer Center Support Grant","award":["P30CA168524"],"award-info":[{"award-number":["P30CA168524"]}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1TR002366"],"award-info":[{"award-number":["UL1TR002366"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1TR002366"],"award-info":[{"award-number":["UL1TR002366"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIH","award":["R01AG064227"],"award-info":[{"award-number":["R01AG064227"]}]},{"name":"NIH","award":["R01AG064227"],"award-info":[{"award-number":["R01AG064227"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Multi-omic studies provide comprehensive insight into biological systems by evaluating cellular changes between normal and pathological conditions at multiple levels of measurement. Biological networks, which represent interactions or associations between biomolecules, have been highly effective in facilitating omic analysis. However, current network-based methods lack generalizability to accommodate multiple data types across a range of diverse experiments.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We present AMEND 2.0, an updated active module identification method which can analyze multiplex and\/or heterogeneous networks integrated with multi-omic data in a highly generalizable framework, in contrast to existing methods, which are mostly appropriate for at most two specific omic types. It is powered by Random Walk with Restart for multiplex-heterogeneous networks, with additional capabilities including degree bias adjustment and biased random walk for multi-objective module identification. AMEND was applied to two real-world multi-omic datasets: renal cell carcinoma data from The cancer genome atlas and an O-GlcNAc Transferase knockout study. Additional analyses investigate the performance of various subroutines of AMEND on tasks of node ranking and degree bias adjustment.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>While the analysis of multi-omic datasets in a network context is poised to provide deeper understanding of health and disease, new methods are required to fully take advantage of this increasingly complex data. The current study combines several network analysis techniques into a single versatile method for analyzing biological networks with multi-omic data that can be applied in many diverse scenarios. Software is freely available in the R programming language at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/samboyd0\/AMEND\" ext-link-type=\"uri\">https:\/\/github.com\/samboyd0\/AMEND<\/jats:ext-link>.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/s12859-025-06063-x","type":"journal-article","created":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T12:43:48Z","timestamp":1738759428000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AMEND 2.0: module identification and multi-omic data integration with multiplex-heterogeneous graphs"],"prefix":"10.1186","volume":"26","author":[{"given":"Samuel S.","family":"Boyd","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chad","family":"Slawson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey A.","family":"Thompson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,5]]},"reference":[{"issue":"7283","key":"6063_CR1","doi-asserted-by":"publisher","first-page":"899","DOI":"10.1038\/nature08822","volume":"463","author":"R Beroukhim","year":"2010","unstructured":"Beroukhim R, et al. The landscape of somatic copy-number alteration across human cancers. Nature. 2010;463(7283):899\u2013905.","journal-title":"Nature"},{"key":"6063_CR2","doi-asserted-by":"crossref","unstructured":"Cancer Genome Atlas N. Genomic classification of cutaneous melanoma. Cell 2015;161(7):1681\u201396.","DOI":"10.1016\/j.cell.2015.05.044"},{"issue":"1","key":"6063_CR3","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1186\/2049-2618-1-17","volume":"1","author":"IH McHardy","year":"2013","unstructured":"McHardy IH, et al. Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships. Microbiome. 2013;1(1):17.","journal-title":"Microbiome"},{"issue":"2","key":"6063_CR4","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1038\/nrg3868","volume":"16","author":"MD Ritchie","year":"2015","unstructured":"Ritchie MD, et al. Methods of integrating data to uncover genotype-phenotype interactions. Nat Rev Genet. 2015;16(2):85\u201397.","journal-title":"Nat Rev Genet"},{"issue":"6","key":"6063_CR5","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1002\/wsbm.144","volume":"3","author":"J Loscalzo","year":"2011","unstructured":"Loscalzo J, Barabasi AL. Systems biology and the future of medicine. Wiley Interdiscip Rev Syst Biol Med. 2011;3(6):619\u201327.","journal-title":"Wiley Interdiscip Rev Syst Biol Med"},{"issue":"2","key":"6063_CR6","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1038\/nrg1272","volume":"5","author":"AL Barabasi","year":"2004","unstructured":"Barabasi AL, Oltvai ZN. Network biology: understanding the cell\u2019s functional organization. Nat Rev Genet. 2004;5(2):101\u201313.","journal-title":"Nat Rev Genet"},{"key":"6063_CR7","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1186\/1756-0381-4-19","volume":"4","author":"S Erten","year":"2011","unstructured":"Erten S, et al. DADA: degree-aware algorithms for network-based disease gene prioritization. BioData Min. 2011;4:19.","journal-title":"BioData Min"},{"issue":"3","key":"6063_CR8","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1038\/nmeth.2810","volume":"11","author":"B Wang","year":"2014","unstructured":"Wang B, et al. Similarity network fusion for aggregating data types on a genomic scale. Nat Methods. 2014;11(3):333\u20137.","journal-title":"Nat Methods"},{"issue":"1","key":"6063_CR9","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1186\/s12859-023-05376-z","volume":"24","author":"SS Boyd","year":"2023","unstructured":"Boyd SS, Slawson C, Thompson JA. AMEND: active module identification using experimental data and network diffusion. BMC Bioinformatics. 2023;24(1):277.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"6063_CR10","doi-asserted-by":"publisher","DOI":"10.15252\/msb.20209593","volume":"17","author":"H Levi","year":"2021","unstructured":"Levi H, Elkon R, Shamir R. DOMINO: a network-based active module identification algorithm with reduced rate of false calls. Mol Syst Biol. 2021;17(1): e9593.","journal-title":"Mol Syst Biol"},{"issue":"4","key":"6063_CR11","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1004879","volume":"12","author":"N Tuncbag","year":"2016","unstructured":"Tuncbag N, et al. Network-based interpretation of diverse high-throughput datasets through the omics integrator software package. PLoS Comput Biol. 2016;12(4): e1004879.","journal-title":"PLoS Comput Biol"},{"issue":"9","key":"6063_CR12","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1038\/nrg.2017.38","volume":"18","author":"L Cowen","year":"2017","unstructured":"Cowen L, et al. Network propagation: a universal amplifier of genetic associations. Nat Rev Genet. 2017;18(9):551\u201362.","journal-title":"Nat Rev Genet"},{"key":"6063_CR13","doi-asserted-by":"publisher","first-page":"106","DOI":"10.3389\/fgene.2020.00106","volume":"11","author":"N Di Nanni","year":"2020","unstructured":"Di Nanni N, et al. Network diffusion promotes the integrative analysis of multiple omics. Front Genet. 2020;11:106.","journal-title":"Front Genet"},{"key":"6063_CR14","doi-asserted-by":"crossref","unstructured":"Cancer Genome Atlas Research N. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 2013;499(7456):43\u20139.","DOI":"10.1038\/nature12222"},{"issue":"11","key":"6063_CR15","doi-asserted-by":"publisher","first-page":"1713","DOI":"10.1162\/neco_a_01611","volume":"35","author":"E Seabrook","year":"2023","unstructured":"Seabrook E, Wiskott L. A tutorial on the spectral theory of markov chains. Neural Comput. 2023;35(11):1713\u201396.","journal-title":"Neural Comput"},{"issue":"1\u20137","key":"6063_CR16","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/S0169-7552(98)00110-X","volume":"30","author":"S Brin","year":"1998","unstructured":"Brin S, Page L. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and Isdn Systems. 1998;30(1\u20137):107\u201317.","journal-title":"Computer Networks and Isdn Systems"},{"key":"6063_CR17","doi-asserted-by":"publisher","first-page":"4","DOI":"10.3389\/fgene.2019.00004","volume":"10","author":"H Biran","year":"2019","unstructured":"Biran H, Kupiec M, Sharan R. Comparative analysis of normalization methods for network propagation. Front Genet. 2019;10:4.","journal-title":"Front Genet"},{"issue":"9","key":"6063_CR18","doi-asserted-by":"publisher","first-page":"3400","DOI":"10.1016\/j.laa.2011.11.034","volume":"436","author":"B Mourad","year":"2012","unstructured":"Mourad B. On a spectral property of doubly stochastic matrices and its application to their inverse eigenvalue problem. Linear Algebra Appl. 2012;436(9):3400\u201312.","journal-title":"Linear Algebra Appl"},{"key":"6063_CR19","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1137\/040608635","volume":"30","author":"S Dongen","year":"2008","unstructured":"Dongen S. Graph clustering via a discrete uncoupling process. SIAM J Matrix Anal Appl. 2008;30:121\u201341.","journal-title":"SIAM J. Matrix Anal. Appl."},{"issue":"1","key":"6063_CR20","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1000641","volume":"6","author":"O Vanunu","year":"2010","unstructured":"Vanunu O, et al. Associating genes and protein complexes with disease via network propagation. PLoS Comput Biol. 2010;6(1): e1000641.","journal-title":"PLoS Comput Biol"},{"key":"6063_CR21","doi-asserted-by":"crossref","unstructured":"Griffin ME, et al. Functional glycoproteomics by integrated network assembly and partitioning. bioRxiv, 2023.","DOI":"10.1101\/2023.06.13.541482"},{"issue":"2","key":"6063_CR22","doi-asserted-by":"publisher","first-page":"R29","DOI":"10.1186\/gb-2014-15-2-r29","volume":"15","author":"CW Law","year":"2014","unstructured":"Law CW, et al. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014;15(2):R29.","journal-title":"Genome Biol"},{"issue":"7","key":"6063_CR23","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkv007","volume":"43","author":"ME Ritchie","year":"2015","unstructured":"Ritchie ME, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47\u2013e47.","journal-title":"Nucleic Acids Res"},{"issue":"4","key":"6063_CR24","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1093\/bioinformatics\/btu684","volume":"31","author":"G Yu","year":"2015","unstructured":"Yu G, et al. DOSE: an R\/Bioconductor package for disease ontology semantic and enrichment analysis. Bioinformatics. 2015;31(4):608\u20139.","journal-title":"Bioinformatics"},{"issue":"1","key":"6063_CR25","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1038\/s42005-022-00937-9","volume":"5","author":"A Baptista","year":"2022","unstructured":"Baptista A, Gonzalez A, Baudot A. Universal multilayer network exploration by random walk with restart. Commun Phys. 2022;5(1):170.","journal-title":"Commun Phys."},{"issue":"9","key":"6063_CR26","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1093\/bioinformatics\/btq108","volume":"26","author":"Y Li","year":"2010","unstructured":"Li Y, Patra JC. Genome-wide inferring gene-phenotype relationship by walking on the heterogeneous network. Bioinformatics. 2010;26(9):1219\u201324.","journal-title":"Bioinformatics"},{"issue":"3","key":"6063_CR27","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1093\/bioinformatics\/bty637","volume":"35","author":"A Valdeolivas","year":"2019","unstructured":"Valdeolivas A, et al. Random walk with restart on multiplex and heterogeneous biological networks. Bioinformatics. 2019;35(3):497\u2013505.","journal-title":"Bioinformatics"},{"issue":"1","key":"6063_CR28","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1093\/nar\/28.1.27","volume":"28","author":"M Kanehisa","year":"2000","unstructured":"Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27\u201330.","journal-title":"Nucleic Acids Res"},{"key":"6063_CR29","doi-asserted-by":"publisher","first-page":"260","DOI":"10.3389\/fgene.2015.00260","volume":"6","author":"MH Schaefer","year":"2015","unstructured":"Schaefer MH, Serrano L, Andrade-Navarro MA. Correcting for the study bias associated with protein-protein interaction measurements reveals differences between protein degree distributions from different cancer types. Front Genet. 2015;6:260.","journal-title":"Front Genet"},{"issue":"17","key":"6063_CR30","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkaa639","volume":"48","author":"G Barel","year":"2020","unstructured":"Barel G, Herwig R. NetCore: a network propagation approach using node coreness. Nucleic Acids Res. 2020;48(17): e98.","journal-title":"Nucleic Acids Res"},{"issue":"3","key":"6063_CR31","doi-asserted-by":"publisher","first-page":"907","DOI":"10.1214\/aoms\/1177696968","volume":"41","author":"SE Fienberg","year":"1970","unstructured":"Fienberg SE. An iterative procedure for estimation in contingency tables. Ann Math Stat. 1970;41(3):907\u20130.","journal-title":"Ann Math Stat"},{"issue":"Database issue","key":"6063_CR32","doi-asserted-by":"publisher","first-page":"D691","DOI":"10.1093\/nar\/gkq1018","volume":"39","author":"D Croft","year":"2011","unstructured":"Croft D, et al. Reactome: a database of reactions, pathways and biological processes. Nucleic Acids Res. 2011;39(Database issue):D691-7.","journal-title":"Nucleic Acids Res."},{"issue":"D1","key":"6063_CR33","doi-asserted-by":"publisher","first-page":"D607","DOI":"10.1093\/nar\/gky1131","volume":"47","author":"D Szklarczyk","year":"2019","unstructured":"Szklarczyk D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607\u201313.","journal-title":"Nucleic Acids Res"},{"issue":"Database issue","key":"6063_CR34","first-page":"991","volume":"41","author":"T Barrett","year":"2013","unstructured":"Barrett T, et al. NCBI GEO: archive for functional genomics data sets\u2013update. Nucleic Acids Res. 2013;41(Database issue):991\u20135.","journal-title":"Nucleic Acids Res"},{"issue":"6833","key":"6063_CR35","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/35075138","volume":"411","author":"H Jeong","year":"2001","unstructured":"Jeong H, et al. Lethality and centrality in protein networks. Nature. 2001;411(6833):41\u20132.","journal-title":"Nature"},{"key":"6063_CR36","unstructured":"Team RC. R: a language and environment for statistical computing, in R foundation for statistical computing. Vienna, Austria; 2023"},{"key":"6063_CR37","doi-asserted-by":"crossref","unstructured":"Cancer Genome Atlas Research N, et al. The cancer genome atlas pan-cancer analysis project. Nat Genet. 2013;45(10):1113\u201320.","DOI":"10.1038\/ng.2764"},{"key":"6063_CR38","unstructured":"Center BITGDA. Firehose stddata 2016 01 28 run, B.I.o.M.a. Harvard, Editor; 2016."},{"issue":"14","key":"6063_CR39","doi-asserted-by":"publisher","first-page":"i190","DOI":"10.1093\/bioinformatics\/btx252","volume":"33","author":"M Zitnik","year":"2017","unstructured":"Zitnik M, Leskovec J. Predicting multicellular function through multi-layer tissue networks. Bioinformatics. 2017;33(14):i190\u20138.","journal-title":"Bioinformatics"},{"issue":"14","key":"6063_CR40","doi-asserted-by":"publisher","first-page":"2233","DOI":"10.1093\/bioinformatics\/btw216","volume":"32","author":"A Lachmann","year":"2016","unstructured":"Lachmann A, et al. ARACNe-AP: gene network reverse engineering through adaptive partitioning inference of mutual information. Bioinformatics. 2016;32(14):2233\u20135.","journal-title":"Bioinformatics"},{"key":"6063_CR41","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/1471-2105-13-20","volume":"13","author":"G Sales","year":"2012","unstructured":"Sales G, et al. graphite\u2014a Bioconductor package to convert pathway topology to gene network. BMC Bioinformatics. 2012;13:20.","journal-title":"BMC Bioinformatics"},{"issue":"D1","key":"6063_CR42","doi-asserted-by":"publisher","first-page":"D222","DOI":"10.1093\/nar\/gkab1079","volume":"50","author":"HY Huang","year":"2022","unstructured":"Huang HY, et al. miRTarBase update 2022: an informative resource for experimentally validated miRNA-target interactions. Nucleic Acids Res. 2022;50(D1):D222\u201330.","journal-title":"Nucleic Acids Res"},{"issue":"9","key":"6063_CR43","doi-asserted-by":"publisher","first-page":"7825","DOI":"10.3390\/ijms24097825","volume":"24","author":"T Kalantzakos","year":"2023","unstructured":"Kalantzakos T, et al. MicroRNA-155-5p targets JADE-1, promoting proliferation, migration, and invasion in clear cell renal cell carcinoma cells. Int J Mol Sci. 2023;24(9):7825.","journal-title":"Int J Mol Sci"},{"issue":"3","key":"6063_CR44","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1016\/j.juro.2011.04.110","volume":"186","author":"NM White","year":"2011","unstructured":"White NM, et al. miRNA profiling for clear cell renal cell carcinoma: biomarker discovery and identification of potential controls and consequences of miRNA dysregulation. J Urol. 2011;186(3):1077\u201383.","journal-title":"J Urol"},{"issue":"10","key":"6063_CR45","doi-asserted-by":"publisher","first-page":"2617","DOI":"10.1158\/1078-0432.CCR-13-3224","volume":"20","author":"X Chen","year":"2014","unstructured":"Chen X, et al. miR-141 is a key regulator of renal cell carcinoma proliferation and metastasis by controlling EphA2 expression. Clin Cancer Res. 2014;20(10):2617\u201330.","journal-title":"Clin Cancer Res"},{"issue":"4","key":"6063_CR46","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1002\/path.2437","volume":"216","author":"C Nakada","year":"2008","unstructured":"Nakada C, et al. Genome-wide microRNA expression profiling in renal cell carcinoma: significant down-regulation of miR-141 and miR-200c. J Pathol. 2008;216(4):418\u201327.","journal-title":"J Pathol"},{"key":"6063_CR47","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1186\/1752-0509-4-51","volume":"4","author":"H Liu","year":"2010","unstructured":"Liu H, et al. Identifying mRNA targets of microRNA dysregulated in cancer: with application to clear cell renal cell carcinoma. BMC Syst Biol. 2010;4:51.","journal-title":"BMC Syst Biol"},{"issue":"5","key":"6063_CR48","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1038\/bjc.2013.56","volume":"108","author":"RI McCormick","year":"2013","unstructured":"McCormick RI, et al. miR-210 is a target of hypoxia-inducible factors 1 and 2 in renal cancer, regulates ISCU and correlates with good prognosis. Br J Cancer. 2013;108(5):1133\u201342.","journal-title":"Br J Cancer"},{"issue":"4","key":"6063_CR49","doi-asserted-by":"publisher","first-page":"966.e1","DOI":"10.1016\/j.urology.2011.12.011","volume":"79","author":"D Shang","year":"2012","unstructured":"Shang D, et al. TGFBI-promoted adhesion, migration and invasion of human renal cell carcinoma depends on inactivation of von Hippel-Lindau tumor suppressor. Urology. 2012;79(4):966.e1-7.","journal-title":"Urology"},{"issue":"4","key":"6063_CR50","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/BF00942091","volume":"25","author":"K Tanabe","year":"1997","unstructured":"Tanabe K, et al. Molecular regulation of intercellular adhesion molecule 1 (ICAM-1) expression in renal cell carcinoma. Urol Res. 1997;25(4):231\u20138.","journal-title":"Urol Res"},{"key":"6063_CR51","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/1472-6890-9-9","volume":"9","author":"AA Williams","year":"2009","unstructured":"Williams AA, et al. CD 9 and vimentin distinguish clear cell from chromophobe renal cell carcinoma. BMC Clin Pathol. 2009;9:9.","journal-title":"BMC Clin Pathol"},{"issue":"1","key":"6063_CR52","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/75556","volume":"25","author":"M Ashburner","year":"2000","unstructured":"Ashburner M, et al. Gene ontology: tool for the unification of biology. Gene Ontol Consort Nat Genet. 2000;25(1):25\u20139.","journal-title":"Gene Ontol Consort Nat Genet"},{"key":"6063_CR53","unstructured":"Gene Ontology C, et al. The Gene Ontology knowledgebase in 2023. Genetics. 2023;224(1):iyad031."},{"issue":"1","key":"6063_CR54","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/S0092-8674(00)81683-9","volume":"100","author":"D Hanahan","year":"2000","unstructured":"Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100(1):57\u201370.","journal-title":"Cell"},{"issue":"4","key":"6063_CR55","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1016\/j.cell.2017.04.016","volume":"169","author":"S Chevrier","year":"2017","unstructured":"Chevrier S, et al. An immune atlas of clear cell renal cell carcinoma. Cell. 2017;169(4):736-49.e18.","journal-title":"Cell"},{"issue":"D1","key":"6063_CR56","doi-asserted-by":"publisher","first-page":"D1305","DOI":"10.1093\/nar\/gkad1051","volume":"52","author":"JA Baron","year":"2024","unstructured":"Baron JA, et al. The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem. Nucleic Acids Res. 2024;52(D1):D1305\u201314.","journal-title":"Nucleic Acids Res"},{"issue":"17","key":"6063_CR57","doi-asserted-by":"publisher","first-page":"3055","DOI":"10.1093\/bioinformatics\/bty1054","volume":"35","author":"A Singh","year":"2019","unstructured":"Singh A, et al. DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays. Bioinformatics. 2019;35(17):3055\u201362.","journal-title":"Bioinformatics"},{"issue":"2","key":"6063_CR58","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.cmet.2014.07.014","volume":"20","author":"S Hardiville","year":"2014","unstructured":"Hardiville S, Hart GW. Nutrient regulation of signaling, transcription, and cell physiology by O-GlcNAcylation. Cell Metab. 2014;20(2):208\u201313.","journal-title":"Cell Metab"},{"key":"6063_CR59","unstructured":"Zachara NE et al. The O-GlcNAc modification. In: Varki A et al., editors. Essentials of Glycobiology. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press; 2022"},{"key":"6063_CR60","doi-asserted-by":"publisher","DOI":"10.3389\/fbinf.2022.893032","volume":"2","author":"L Neums","year":"2022","unstructured":"Neums L, et al. Assessing equivalent and inverse change in genes between diverse experiments. Front Bioinform. 2022;2: 893032.","journal-title":"Front Bioinform"},{"issue":"1","key":"6063_CR61","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1186\/s12864-020-6589-x","volume":"21","author":"JA Thompson","year":"2020","unstructured":"Thompson JA, Koestler DC. Equivalent change enrichment analysis: assessing equivalent and inverse change in biological pathways between diverse experiments. BMC Genomics. 2020;21(1):180.","journal-title":"BMC Genomics"},{"issue":"D1","key":"6063_CR62","doi-asserted-by":"publisher","first-page":"D380","DOI":"10.1093\/nar\/gkv1277","volume":"44","author":"D Szklarczyk","year":"2016","unstructured":"Szklarczyk D, et al. STITCH 5: augmenting protein-chemical interaction networks with tissue and affinity data. Nucleic Acids Res. 2016;44(D1):D380\u20134.","journal-title":"Nucleic Acids Res"},{"issue":"2","key":"6063_CR63","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1097\/MOG.0b013e32834e7b4b","volume":"28","author":"KD Corbin","year":"2012","unstructured":"Corbin KD, Zeisel SH. Choline metabolism provides novel insights into nonalcoholic fatty liver disease and its progression. Curr Opin Gastroenterol. 2012;28(2):159\u201365.","journal-title":"Curr Opin Gastroenterol"},{"issue":"3","key":"6063_CR64","doi-asserted-by":"publisher","first-page":"2142","DOI":"10.3390\/ijms24032142","volume":"24","author":"Z Xie","year":"2023","unstructured":"Xie Z, et al. Emerging role of protein O-GlcNAcylation in liver metabolism: implications for diabetes and NAFLD. Int J Mol Sci. 2023;24(3):2142.","journal-title":"Int J Mol Sci"},{"issue":"5","key":"6063_CR65","doi-asserted-by":"publisher","first-page":"1143","DOI":"10.1016\/j.molcel.2019.11.022","volume":"77","author":"S Hardiville","year":"2020","unstructured":"Hardiville S, et al. TATA-box binding protein O-GlcNAcylation at T114 regulates formation of the B-TFIID complex and is critical for metabolic gene regulation. Mol Cell. 2020;77(5):1143-1152.e7.","journal-title":"Mol Cell"},{"issue":"Database issue","key":"6063_CR66","doi-asserted-by":"publisher","first-page":"D433","DOI":"10.1093\/nar\/gki005","volume":"33","author":"C von Mering","year":"2005","unstructured":"von Mering C, et al. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005;33(Database issue):D433-7.","journal-title":"Nucleic Acids Res."},{"key":"6063_CR67","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1016\/j.csbj.2022.11.050","volume":"21","author":"E Athieniti","year":"2023","unstructured":"Athieniti E, Spyrou GM. A guide to multi-omics data collection and integration for translational medicine. Comput Struct Biotechnol J. 2023;21:134\u201349.","journal-title":"Comput Struct Biotechnol J"},{"key":"6063_CR68","unstructured":"Boyd SS. Multi-omic data integration and active module identification on molecular interaction networks. University of Kansas\u2009ProQuest Dissertations & Theses; 2024."}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-025-06063-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-025-06063-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-025-06063-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T16:13:08Z","timestamp":1738771988000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-025-06063-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,5]]},"references-count":68,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["6063"],"URL":"https:\/\/doi.org\/10.1186\/s12859-025-06063-x","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,5]]},"assertion":[{"value":"12 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"39"}}