{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T06:33:11Z","timestamp":1769322791966,"version":"3.49.0"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Graduate Student Innovation Fund of Xi'an University of Posts and Telecommunications","award":["CXJJYL2024054"],"award-info":[{"award-number":["CXJJYL2024054"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Membr Comput"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s41965-025-00205-z","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T03:08:21Z","timestamp":1755572901000},"page":"405-428","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A high-order SNP epistasis detection method based on membrane computing and multi-objective ant colony optimization"],"prefix":"10.1007","volume":"7","author":[{"given":"Ting","family":"Fan","sequence":"first","affiliation":[]},{"given":"Shouheng","family":"Tuo","sequence":"additional","affiliation":[]},{"given":"Yong","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"key":"205_CR1","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.ajhg.2017.06.005","volume":"101","author":"PM Visscher","year":"2017","unstructured":"Visscher, P. M., Wray, N. R., Zhang, Q., et al. (2017). 10 years of GWAS discovery: Biology, function, and translation. American Journal of Human Genetics, 101, 5\u201322.","journal-title":"American Journal of Human Genetics"},{"key":"205_CR2","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1038\/s41576-019-0127-1","volume":"20","author":"V Tam","year":"2019","unstructured":"Tam, V., Patel, N., Turcotte, M., et al. (2019). Benefits and limitations of genome-wide association studies. Nature Reviews Genetics, 20, 467\u2013484.","journal-title":"Nature Reviews Genetics"},{"key":"205_CR3","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1093\/bioinformatics\/btp713","volume":"26","author":"JH Moore","year":"2010","unstructured":"Moore, J. H., Asselbergs, F. W., & Williams, S. M. (2010). Bioinformatics challenges for genome-wide association studies. Bioinformatics, 26, 445\u2013455.","journal-title":"Bioinformatics"},{"key":"205_CR4","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-1-0716-3024-2_9","volume":"2638","author":"J He","year":"2023","unstructured":"He, J., & Gai, J. (2023). Genome-wide association studies (GWAS). Methods in Molecular Biology, 2638, 123\u2013146. https:\/\/doi.org\/10.1007\/978-1-0716-3024-2_9","journal-title":"Methods in Molecular Biology"},{"key":"205_CR5","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1080\/07853890252953473","volume":"34","author":"JH Moore","year":"2002","unstructured":"Moore, J. H., & Williams, S. M. (2002). New strategies for identifying gene-gene interactions in hypertension. Annals of Medicine, 34, 88\u201395.","journal-title":"Annals of Medicine"},{"key":"205_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1475-2867-10-11","volume":"10","author":"SS Knox","year":"2010","unstructured":"Knox, S. S. (2010). From \u201comics\u201d to complex disease: A systems biology approach to gene-environment interactions in cancer. Cancer Cell International, 10, 1\u201313. https:\/\/doi.org\/10.1186\/1475-2867-10-11","journal-title":"Cancer Cell International"},{"key":"205_CR7","doi-asserted-by":"publisher","first-page":"1934","DOI":"10.1093\/hmg\/ddt581","volume":"23","author":"RL Milne","year":"2014","unstructured":"Milne, R. L., Herranz, J., Michailidou, K., et al. (2014). A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the Breast Cancer Association Consortium. Human Molecular Genetics, 23, 1934\u20131946. https:\/\/doi.org\/10.1093\/hmg\/ddt581","journal-title":"Human Molecular Genetics"},{"key":"205_CR8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000464","volume":"5","author":"W Tang","year":"2009","unstructured":"Tang, W., Wu, X., Jiang, R., & Li, Y. (2009). Epistatic module detection for case-control studies: A Bayesian model with a Gibbs sampling strategy. PLoS Genetics, 5, Article e1000464. https:\/\/doi.org\/10.1371\/journal.pgen.1000464","journal-title":"PLoS Genetics"},{"key":"205_CR9","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1002\/ajmg.b.31017","volume":"153","author":"GS Zubenko","year":"2010","unstructured":"Zubenko, G. S., Hughes, H. B., & Zubenko, W. N. (2010). D10s1423 identifies a susceptibility locus for Alzheimer\u2019s disease (AD7) in a prospective, longitudinal, double-blind study of asymptomatic individuals: Results at 14 years. American Journal of Medical Genetics Part B Neuropsychiatric Genetics, 153, 359\u2013364. https:\/\/doi.org\/10.1002\/ajmg.b.31017","journal-title":"American Journal of Medical Genetics Part B Neuropsychiatric Genetics"},{"key":"205_CR10","doi-asserted-by":"crossref","unstructured":"Gumpinger AC, Roqueiro D, Grimm DG, Borgwardt KM (2018) Methods and tools in genome-wide association studies. In: Methods in molecular biology, pp. 93\u2013136","DOI":"10.1007\/978-1-4939-8618-7_5"},{"key":"205_CR11","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1093\/bioinformatics\/btp622","volume":"26","author":"X Wan","year":"2009","unstructured":"Wan, X., Yang, C., Yang, Q., et al. (2009). Predictive rule inference for epistatic interaction detection in genome-wide association studies. Bioinformatics, 26, 30\u201337. https:\/\/doi.org\/10.1093\/bioinformatics\/btp622","journal-title":"Bioinformatics"},{"key":"205_CR12","doi-asserted-by":"publisher","first-page":"4389","DOI":"10.1093\/bioinformatics\/btaa215","volume":"36","author":"S Tuo","year":"2020","unstructured":"Tuo, S., Liu, H., & Chen, H. (2020). Multipopulation harmony search algorithm for the detection of high-order SNP interactions. Bioinformatics, 36, 4389\u20134398. https:\/\/doi.org\/10.1093\/bioinformatics\/btaa215","journal-title":"Bioinformatics"},{"key":"205_CR13","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1109\/TCBB.2016.2635125","volume":"15","author":"S Uppu","year":"2018","unstructured":"Uppu, S., Krishna, A., & Gopalan, R. P. (2018). A review on methods for detecting SNP interactions in high-dimensional genomic data. IEEE\/ACM Transactions on Computational Biology and Bioinformatics, 15, 599\u2013612.","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"},{"issue":"2","key":"205_CR14","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1109\/TCBB.2020.3030312","volume":"19","author":"C Ponte-Fernandez","year":"2022","unstructured":"Ponte-Fernandez, C., Gonzalez-Dominguez, J., Carvajal-Rodriguez, A., & Martin, M. J. (2022). Evaluation of existing methods for high-order epistasis detection. IEEE\/ACM Transactions on Computational Biology and Bioinformatics, 19(2), 912\u2013926. https:\/\/doi.org\/10.1109\/TCBB.2020.3030312","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"},{"key":"205_CR15","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1016\/j.ajhg.2010.07.021","volume":"87","author":"X Wan","year":"2010","unstructured":"Wan, X., Yang, C., Yang, Q., et al. (2010). BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies. American Journal of Human Genetics, 87, 325\u2013340. https:\/\/doi.org\/10.1016\/j.ajhg.2010.07.021","journal-title":"American Journal of Human Genetics"},{"key":"205_CR16","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.1093\/bioinformatics\/btu840","volume":"31","author":"G Yang","year":"2015","unstructured":"Yang, G., Jiang, W., Yang, Q., & Yu, W. (2015). PBOOST: A GPU-based tool for parallel permutation tests in genome-wide association studies. Bioinformatics, 31, 1460\u20131462. https:\/\/doi.org\/10.1093\/bioinformatics\/btu840","journal-title":"Bioinformatics"},{"key":"205_CR17","doi-asserted-by":"publisher","first-page":"1462","DOI":"10.1093\/bioinformatics\/btr172","volume":"27","author":"G Hemani","year":"2011","unstructured":"Hemani, G., Theocharidis, A., Wei, W., & Haley, C. (2011). EpiGPU: Exhaustive pairwise epistasis scans parallelized on consumer level graphics cards. Bioinformatics, 27, 1462\u20131465. https:\/\/doi.org\/10.1093\/bioinformatics\/btr172","journal-title":"Bioinformatics"},{"key":"205_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1756-0500-3-117","volume":"3","author":"Y Wang","year":"2010","unstructured":"Wang, Y., Liu, X., Robbins, K., & Rekaya, R. (2010). AntEpiSeeker: Detecting epistatic interactions for case-control studies using a two-stage ant colony optimization algorithm. BMC Research Notes, 3, 1\u20138. https:\/\/doi.org\/10.1186\/1756-0500-3-117","journal-title":"BMC Research Notes"},{"key":"205_CR19","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1093\/bioinformatics\/btn652","volume":"25","author":"C Yang","year":"2009","unstructured":"Yang, C., He, Z., Wan, X., et al. (2009). SNPHarvester: A filtering-based approach for detecting epistatic interactions in genome-wide association studies. Bioinformatics, 25, 504\u2013511. https:\/\/doi.org\/10.1093\/bioinformatics\/btn652","journal-title":"Bioinformatics"},{"key":"205_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.dsp.2013.08.007","volume":"24","author":"J Shang","year":"2014","unstructured":"Shang, J., Zhang, J., Sun, Y., & Zhang, Y. (2014). EpiMiner: A three-stage co-information based method for detecting and visualizing epistatic interactions. Digit Signal Process A Rev J, 24, 1\u201313. https:\/\/doi.org\/10.1016\/j.dsp.2013.08.007","journal-title":"Digit Signal Process A Rev J"},{"issue":"9","key":"205_CR21","doi-asserted-by":"publisher","DOI":"10.3390\/genes9090435","volume":"9","author":"S Tuo","year":"2018","unstructured":"Tuo, S. (2018). FDHE-IW: A fast approach for detecting high-order epistasis in genome-wide case-control studies. Genes, 9(9), Article 435. https:\/\/doi.org\/10.3390\/genes9090435","journal-title":"Genes"},{"key":"205_CR22","doi-asserted-by":"publisher","first-page":"11529","DOI":"10.1038\/s41598-017-11064-9","volume":"7","author":"S Tuo","year":"2017","unstructured":"Tuo, S., Zhang, J., Yuan, X., et al. (2017). Niche harmony search algorithm for detecting complex disease associated high-order SNP combinations. Scientific Reports, 7, 11529. https:\/\/doi.org\/10.1038\/s41598-017-11064-9","journal-title":"Scientific Reports"},{"key":"205_CR23","doi-asserted-by":"publisher","first-page":"13497","DOI":"10.1109\/ACCESS.2019.2894676","volume":"7","author":"J Shang","year":"2019","unstructured":"Shang, J., Wang, X., Wu, X., et al. (2019). A review of ant colony optimization based methods for detecting epistatic interactions. IEEE Access, 7, 13497\u201313509. https:\/\/doi.org\/10.1109\/ACCESS.2019.2894676","journal-title":"IEEE Access"},{"key":"205_CR24","doi-asserted-by":"publisher","first-page":"2354","DOI":"10.1093\/bioinformatics\/btx163","volume":"33","author":"CH Yang","year":"2017","unstructured":"Yang, C. H., Chuang, L. Y., & Lin, Y. D. (2017). CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies. Bioinformatics, 33, 2354\u20132362. https:\/\/doi.org\/10.1093\/bioinformatics\/btx163","journal-title":"Bioinformatics"},{"key":"205_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/genes12020191","volume":"12","author":"Y Chen","year":"2021","unstructured":"Chen, Y., Xu, F., Pian, C., et al. (2021). Epimoga: An epistasis detection method based on a multi-objective genetic algorithm. Genes (Basel), 12, 1\u201318. https:\/\/doi.org\/10.3390\/genes12020191","journal-title":"Genes (Basel)"},{"key":"205_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13040-017-0143-7","volume":"10","author":"Y Sun","year":"2017","unstructured":"Sun, Y., Shang, J., Liu, J. X., et al. (2017). EpiACO: A method for identifying epistasis based on ant Colony optimization algorithm. BioData Mining, 10, 1\u201317. https:\/\/doi.org\/10.1186\/s13040-017-0143-7","journal-title":"BioData Mining"},{"key":"205_CR27","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1093\/bioinformatics\/btu702","volume":"31","author":"PJ Jing","year":"2015","unstructured":"Jing, P. J., & Shen, H. B. (2015). MACOED: A multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies. Bioinformatics, 31, 634\u2013641. https:\/\/doi.org\/10.1093\/bioinformatics\/btu702","journal-title":"Bioinformatics"},{"key":"205_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/genes12020191","volume":"12","author":"Y Chen","year":"2021","unstructured":"Chen, Y., Xu, F., Pian, C., et al. (2021). Epimoga: An epistasis detection method based on a multi-objective genetic algorithm. Genes, 12, 1\u201318. https:\/\/doi.org\/10.3390\/genes12020191","journal-title":"Genes"},{"key":"205_CR29","doi-asserted-by":"publisher","first-page":"11","DOI":"10.3390\/genes15010011","volume":"15","author":"F Ren","year":"2024","unstructured":"Ren, F., Li, S., Wen, Z., et al. (2024). The spherical evolutionary multi-objective (SEMO) algorithm for identifying disease multi-locus SNP interactions. Genes (Basel), 15, 11. https:\/\/doi.org\/10.3390\/genes15010011","journal-title":"Genes (Basel)"},{"key":"205_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12864-024-10373-4","volume":"25","author":"DY Tang","year":"2024","unstructured":"Tang, D. Y., Mao, Y. J., Zhao, J., et al. (2024). SEEI: Spherical evolution with feedback mechanism for identifying epistatic interactions. BMC Genomics, 25, 1\u201323. https:\/\/doi.org\/10.1186\/s12864-024-10373-4","journal-title":"BMC Genomics"},{"key":"205_CR31","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1007\/s40747-022-00813-7","volume":"9","author":"S Tuo","year":"2023","unstructured":"Tuo, S., Li, C., Liu, F., et al. (2023). MTHSA-DHEI: Multitasking harmony search algorithm for detecting high-order SNP epistatic interactions. Complex Intelligent Systems, 9, 637\u2013658. https:\/\/doi.org\/10.1007\/s40747-022-00813-7","journal-title":"Complex Intelligent Systems"},{"key":"205_CR32","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1007\/s12539-022-00530-2","volume":"14","author":"S Tuo","year":"2022","unstructured":"Tuo, S., Li, C., Liu, F., et al. (2022). A novel multitasking ant colony optimization method for detecting multiorder SNP interactions. Interdisciplinary Sciences, Computational Life Sciences, 14, 814\u2013832. https:\/\/doi.org\/10.1007\/s12539-022-00530-2","journal-title":"Interdisciplinary Sciences, Computational Life Sciences"},{"key":"205_CR33","doi-asserted-by":"publisher","DOI":"10.1007\/s12539-024-00621-2","author":"S Tuo","year":"2024","unstructured":"Tuo, S., & Jiang, J. (2024). A novel detection method for high-order SNP epistatic interactions based on explicit-encoding-based multitasking harmony search. Interdisciplinary Sciences: Computational Life Sciences. https:\/\/doi.org\/10.1007\/s12539-024-00621-2","journal-title":"Interdisciplinary Sciences: Computational Life Sciences"},{"key":"205_CR34","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.biosystems.2006.02.001","volume":"85","author":"G P\u01ceun","year":"2006","unstructured":"P\u01ceun, G., & P\u00e9rez-Jim\u00e9nez, M. J. (2006). Membrane computing: Brief introduction, recent results and applications. Bio Systems, 85, 11\u201322. https:\/\/doi.org\/10.1016\/j.biosystems.2006.02.001","journal-title":"Bio Systems"},{"key":"205_CR35","doi-asserted-by":"publisher","first-page":"3382","DOI":"10.1007\/s11227-023-05592-7","volume":"80","author":"X Gu","year":"2024","unstructured":"Gu, X., Chen, X., Lu, P., et al. (2024). SiMaLSTM-SNP: Novel semantic relatedness learning model preserving both Siamese networks and membrane computing. Journal of Supercomputing, 80, 3382\u20133411. https:\/\/doi.org\/10.1007\/s11227-023-05592-7","journal-title":"Journal of Supercomputing"},{"key":"205_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3431234","volume":"54","author":"B Song","year":"2021","unstructured":"Song, B., Li, K., Orellana-Mart\u00edn, D., et al. (2021). A survey of nature-inspired computing: Membrane computing. Acm Computing Surveys, 54, 1\u201331.","journal-title":"Acm Computing Surveys"},{"key":"205_CR37","doi-asserted-by":"crossref","unstructured":"P\u0103un, G. (2007) Introduction to membrane computing. In Applications of membrane computing, pp 1\u201342","DOI":"10.1007\/3-540-29937-8_1"},{"key":"205_CR38","unstructured":"\u5218\u5e0c\u7389, \u59dc\u73cd\u59ae, & \u8d75\u7389\u796f. (2018). \u819c\u8ba1\u7b97\u7814\u7a76\u7efc\u8ff0. Shandong Shifan Daxue Xuebao\u202f: Ziran Kexue Ban, 32, 127\u2013128."},{"key":"205_CR39","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1016\/j.ins.2014.04.007","volume":"279","author":"G Zhang","year":"2014","unstructured":"Zhang, G., Gheorghe, M., Pan, L., & P\u00e9rez-Jim\u00e9nez, M. J. (2014). Evolutionary membrane computing: A comprehensive survey and new results. Information Sciences, 279, 528\u2013551.","journal-title":"Information Sciences"},{"key":"205_CR40","unstructured":"\u62d3\u5b88\u6052, \u9093\u65b9\u5b89, \u5468\u6d9b (2011) \u4e00\u79cd\u5229\u7528\u819c\u8ba1\u7b97\u6c42\u89e3\u9ad8\u7ef4\u51fd\u6570\u7684\u5168\u5c40\u4f18\u5316\u7b97\u6cd5 3. \u8ba1\u7b97\u673a\u5de5\u7a0b\u4e0e\u5e94\u7528 47:27\u201330"},{"key":"205_CR41","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1007\/s41965-022-00111-8","volume":"4","author":"S Tuo","year":"2022","unstructured":"Tuo, S., Liu, F., Feng, Z. Y., et al. (2022). Membrane computing with harmony search algorithm for gene selection from expression and methylation data. Journal of Membrane Computing, 4, 293\u2013313. https:\/\/doi.org\/10.1007\/s41965-022-00111-8","journal-title":"Journal of Membrane Computing"},{"key":"205_CR42","doi-asserted-by":"crossref","unstructured":"Tuo, S., Huyan, Y., Fan, T., Zhao, Y. (2024). Membrane computing for iot task offloading: An efficient multi-objective constrained optimization framework. Applied Soft Computing 112560.","DOI":"10.1016\/j.asoc.2024.112560"},{"key":"205_CR43","doi-asserted-by":"publisher","unstructured":"Zhao, J. H., Wang, N., Zhou, P. (2012). Multiobjective bio-inspired algorithm based on membrane computing. In Proceedings\u20142012 international conference on computer science and information processing (CSIP) 2012 473\u2013477. https:\/\/doi.org\/10.1109\/CSIP.2012.6308894","DOI":"10.1109\/CSIP.2012.6308894"},{"key":"205_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2023.101453","volume":"84","author":"Y Tian","year":"2024","unstructured":"Tian, Y., Shao, S., Xie, G., & Zhang, X. (2024). A multi-granularity clustering based evolutionary algorithm for large-scale sparse multi-objective optimization. Swarm Intelligence and Evolutionary Computation, 84, Article 101453. https:\/\/doi.org\/10.1016\/j.swevo.2023.101453","journal-title":"Swarm Intelligence and Evolutionary Computation"},{"key":"205_CR45","unstructured":"Colorni, A., Dorigo, M., Maniezzo, V. (1992). An investigation of some properties of an\" ant algorithm\". Ppsn 92."},{"issue":"80-","key":"205_CR46","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1126\/science.1109557","volume":"308","author":"RJ Klein","year":"2005","unstructured":"Klein, R. J., Zeiss, C., Chew, E. Y., et al. (2005). Complement factor H polymorphism in age-related macular degeneration. Science, 308(80-), 385\u2013389. https:\/\/doi.org\/10.1126\/science.1109557","journal-title":"Science"},{"key":"205_CR47","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1126\/science.1110189","volume":"308","author":"AO Edwards","year":"2005","unstructured":"Edwards, A. O., Ritter, R., Abel, K. J., et al. (2005). Complement factor H polymorphism and age-related macular degeneration. Science, 308, 421\u2013424. https:\/\/doi.org\/10.1126\/science.1110189","journal-title":"Science"},{"key":"205_CR48","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1101\/gr.1239303","volume":"13","author":"P Shannon","year":"2003","unstructured":"Shannon, P., Markiel, A., Ozier, O., et al. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13, 2498\u20132504. https:\/\/doi.org\/10.1101\/gr.1239303","journal-title":"Genome Research"},{"key":"205_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-15-102","volume":"15","author":"X Guo","year":"2014","unstructured":"Guo, X., Meng, Y., Yu, N., & Pan, Y. (2014). Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering. BMC Bioinformatics, 15, 1\u201316. https:\/\/doi.org\/10.1186\/1471-2105-15-102","journal-title":"BMC Bioinformatics"},{"key":"205_CR50","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/524821","volume":"2015","author":"J Shang","year":"2015","unstructured":"Shang, J., Sun, Y., Li, S., et al. (2015). An improved opposition-based learning particle swarm optimization for the detection of SNP-SNP interactions. BioMed Research International, 2015, Article 524821. https:\/\/doi.org\/10.1155\/2015\/524821","journal-title":"BioMed Research International"},{"key":"205_CR51","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1038\/ng1537","volume":"37","author":"J Marchini","year":"2005","unstructured":"Marchini, J., Donnelly, P., & Cardon, L. R. (2005). Genome-wide strategies for detecting multiple loci that influence complex diseases. Nature Genetics, 37, 413\u2013417. https:\/\/doi.org\/10.1038\/ng1537","journal-title":"Nature Genetics"},{"key":"205_CR52","doi-asserted-by":"publisher","DOI":"10.3390\/genes10020114","volume":"10","author":"B Guan","year":"2019","unstructured":"Guan, B., & Zhao, Y. (2019). Self-adjusting ant colony optimization based on information entropy for detecting epistatic interactions. Genes, 10, Article 114. https:\/\/doi.org\/10.3390\/genes10020114","journal-title":"Genes"},{"key":"205_CR53","doi-asserted-by":"crossref","unstructured":"Jiang, R., Tang, W., Wu, X., Fu, W. (2009). A random forest approach to the detection of epistatic interactions in case-control studies. In: BMC Bioinformatics, pp. 1\u201312","DOI":"10.1186\/1471-2105-10-S1-S65"},{"key":"205_CR54","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.bone.2018.04.013","volume":"112","author":"M Barba","year":"2018","unstructured":"Barba, M., Di Pietro, L., Massimi, L., et al. (2018). BBS9 gene in nonsyndromic craniosynostosis: Role of the primary cilium in the aberrant ossification of the suture osteogenic niche. Bone, 112, 58\u201370. https:\/\/doi.org\/10.1016\/j.bone.2018.04.013","journal-title":"Bone"},{"key":"205_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12859-019-3022-z","volume":"20","author":"Y Guo","year":"2019","unstructured":"Guo, Y., Zhong, Z., Yang, C., et al. (2019). Epi-GTBN: An approach of epistasis mining based on genetic tabu algorithm and Bayesian network. BMC Bioinformatics, 20, 1\u201318. https:\/\/doi.org\/10.1186\/s12859-019-3022-z","journal-title":"BMC Bioinformatics"},{"key":"205_CR56","doi-asserted-by":"publisher","first-page":"863","DOI":"10.3390\/ijerph13090863","volume":"13","author":"P Rao","year":"2016","unstructured":"Rao, P., Zhou, Y., Ge, S. Q., et al. (2016). Validation of type 2 diabetes risk variants identified by genome-wide association studies in northern Han Chinese. International Journal of Environmental Research and Public Health, 13, 863. https:\/\/doi.org\/10.3390\/ijerph13090863","journal-title":"International Journal of Environmental Research and Public Health"},{"key":"205_CR57","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000003604","volume":"95","author":"K Xu","year":"2016","unstructured":"Xu, K., Jiang, L., Zhang, M., et al. (2016). Type 2 diabetes risk allele UBE2E2 is associated with decreased glucose-stimulated insulin release in elderly Chinese Han individuals. Medicine, 95, Article e3604. https:\/\/doi.org\/10.1097\/MD.0000000000003604","journal-title":"Medicine"},{"key":"205_CR58","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1016\/j.cell.2020.08.008","volume":"182","author":"D Vuckovic","year":"2020","unstructured":"Vuckovic, D., Bao, E. L., Akbari, P., et al. (2020). The polygenic and monogenic basis of blood traits and diseases. Cell, 182, 1214\u20131231. https:\/\/doi.org\/10.1016\/j.cell.2020.08.008","journal-title":"Cell"},{"key":"205_CR59","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1038\/s43587-021-00051-5","volume":"1","author":"HM D\u00f6nerta\u015f","year":"2021","unstructured":"D\u00f6nerta\u015f, H. M., Fabian, D. K., Fuentealba, M., et al. (2021). Common genetic associations between age-related diseases. Nature Aging, 1, 400\u2013412. https:\/\/doi.org\/10.1038\/s43587-021-00051-5","journal-title":"Nature Aging"},{"key":"205_CR60","doi-asserted-by":"publisher","first-page":"1752","DOI":"10.1038\/ng.3985","volume":"49","author":"MA Ferreira","year":"2017","unstructured":"Ferreira, M. A., Vonk, J. M., Baurecht, H., et al. (2017). Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology. Nature Genetics, 49, 1752\u20131757. https:\/\/doi.org\/10.1038\/ng.3985","journal-title":"Nature Genetics"},{"key":"205_CR61","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2164-15-S9-S20","volume":"15","author":"TL Mah","year":"2014","unstructured":"Mah, T. L., Yap, X. N. A., Limviphuvadh, V., et al. (2014). Novel SNP improves differential survivability and mortality in non-small cell lung cancer patients. BMC Genomics, 15, 1\u20137. https:\/\/doi.org\/10.1186\/1471-2164-15-S9-S20","journal-title":"BMC Genomics"},{"key":"205_CR62","doi-asserted-by":"publisher","first-page":"179","DOI":"10.3389\/fgene.2016.00179","volume":"7","author":"L He","year":"2016","unstructured":"He, L., Kernogitski, Y., Kulminskaya, I., et al. (2016). Pleiotropic meta-analyses of longitudinal studies discover novel genetic variants associated with age-related diseases. Frontiers in Genetics, 7, 179. https:\/\/doi.org\/10.3389\/fgene.2016.00179","journal-title":"Frontiers in Genetics"},{"key":"205_CR63","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1109\/TCBB.2021.3080462","volume":"19","author":"J Wang","year":"2022","unstructured":"Wang, J., Zhang, H., Ren, W., et al. (2022). EpiMC: Detecting epistatic interactions using multiple clusterings. IEEE\/ACM Transactions on Computational Biology and Bioinformatics, 19, 243\u2013254. https:\/\/doi.org\/10.1109\/TCBB.2021.3080462","journal-title":"IEEE\/ACM Transactions on Computational Biology and Bioinformatics"}],"container-title":["Journal of Membrane Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s41965-025-00205-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s41965-025-00205-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s41965-025-00205-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T16:49:04Z","timestamp":1766076544000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s41965-025-00205-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"references-count":63,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["205"],"URL":"https:\/\/doi.org\/10.1007\/s41965-025-00205-z","relation":{},"ISSN":["2523-8906","2523-8914"],"issn-type":[{"value":"2523-8906","type":"print"},{"value":"2523-8914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"23 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 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":"The authors declare that they have no conflicts of interest in this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}