{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T03:17:20Z","timestamp":1784085440937,"version":"3.55.0"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,12,11]],"date-time":"2022-12-11T00:00:00Z","timestamp":1670716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61803257"],"award-info":[{"award-number":["61803257"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Natural Science Foundation of Shanghai","doi-asserted-by":"publisher","award":["18ZR1417200"],"award-info":[{"award-number":["18ZR1417200"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>At present, the study on the pathogenesis of Alzheimer\u2019s disease (AD) by multimodal data fusion analysis has been attracted wide attention. It often has the problems of small sample size and high dimension with the multimodal medical data. In view of the characteristics of multimodal medical data, the existing genetic evolution random neural network cluster (GERNNC) model combine genetic evolution algorithm and neural network for the classification of AD patients and the extraction of pathogenic factors. However, the model does not take into account the non-linear relationship between brain regions and genes and the problem that the genetic evolution algorithm can fall into local optimal solutions, which leads to the overall performance of the model is not satisfactory. In order to solve the above two problems, this paper made some improvements on the construction of fusion features and genetic evolution algorithm in GERNNC model, and proposed an improved genetic evolution random neural network cluster (IGERNNC) model. The IGERNNC model uses mutual information correlation analysis method to combine resting-state functional magnetic resonance imaging data with single nucleotide polymorphism data for the construction of fusion features. Based on the traditional genetic evolution algorithm, elite retention strategy and large variation genetic algorithm are added to avoid the model falling into the local optimal solution. Through multiple independent experimental comparisons, the IGERNNC model can more effectively identify AD patients and extract relevant pathogenic factors, which is expected to become an effective tool in the field of AD research.<\/jats:p>","DOI":"10.1093\/bib\/bbac515","type":"journal-article","created":{"date-parts":[[2022,12,11]],"date-time":"2022-12-11T16:06:45Z","timestamp":1670774805000},"source":"Crossref","is-referenced-by-count":13,"title":["Multimodal data fusion based on IGERNNC algorithm for detecting pathogenic brain regions and genes in Alzheimer\u2019s disease"],"prefix":"10.1093","volume":"24","author":[{"given":"Shuaiqun","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Kong","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiwen","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lulu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gen","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaling","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Shanghai Maritime University , Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,12,11]]},"reference":[{"issue":"18","key":"2023011917143740100_ref1","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1056\/NEJMoa2100708","article-title":"Donanemab in early Alzheimer\u2019s disease","volume":"384","author":"Mintun","year":"2021","journal-title":"N Engl J Med"},{"issue":"3","key":"2023011917143740100_ref2","first-page":"321","article-title":"Alzheimer\u2019s disease facts and figures","volume":"15","author":"Association, A.S","year":"2019","journal-title":"Alzheimers Dement"},{"issue":"6","key":"2023011917143740100_ref3","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1016\/S1474-4422(21)00066-1","article-title":"Clinical diagnosis of Alzheimer\u2019s disease: recommendations of the International Working Group","volume":"20","author":"Dubois","year":"2021","journal-title":"Lancet Neurol"},{"key":"2023011917143740100_ref4","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.jneumeth.2017.12.010","article-title":"Random Forest Feature Selection, Fusion and Ensemble Strategy: Combining Multiple Morphological MRI Measures to Discriminate among healthy elderly, MCI, cMCI and Alzheimer\u2019s disease patients: from the Alzheimer\u2019s disease neuroimaging initiative (ADNI) data","volume":"302","author":"Dimitriadis","year":"2017","journal-title":"J Neurosci Methods"},{"key":"2023011917143740100_ref5","article-title":"Linear discriminant analysis: a detailed tutorial","volume-title":"AI communications","author":"","year":"2017"},{"key":"2023011917143740100_ref6","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.patcog.2016.08.025","article-title":"Joint sparse principal component analysis","volume":"61","author":"Yi","year":"2017","journal-title":"Pattern Recognit"},{"issue":"3","key":"2023011917143740100_ref7","doi-asserted-by":"crossref","first-page":"1608","DOI":"10.1016\/j.neuroimage.2011.12.076","article-title":"A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer\u2019s disease in the ADNI cohort","volume":"60","author":"Meda","year":"2012","journal-title":"Neuroimage"},{"key":"2023011917143740100_ref8","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2020.101656","article-title":"Detecting genetic associations with brain imaging phenotypes in Alzheimer\u2019s disease via a novel structured SCCA approach","volume":"61","author":"Du","year":"2020","journal-title":"Med Image Anal"},{"issue":"2","key":"2023011917143740100_ref9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TBME.2017.2771483","article-title":"Adaptive sparse multiple canonical correlation analysis with application to imaging (epi) genomics study of schizophrenia","volume":"65","author":"Hu","year":"2017","journal-title":"IEEE Trans Biomed Eng"},{"key":"2023011917143740100_ref10","doi-asserted-by":"crossref","first-page":"30528","DOI":"10.1109\/ACCESS.2021.3059520","article-title":"An improved multi-task sparse canonical correlation analysis of imaging genetics for detecting biomarkers of Alzheimer\u2019s disease","volume":"9","author":"Wei","year":"2021","journal-title":"IEEE Access"},{"key":"2023011917143740100_ref11","doi-asserted-by":"crossref","first-page":"192","DOI":"10.3389\/fnhum.2010.00192","article-title":"A hybrid machine learning method for fusing fMRI and genetic data: combining both improves classification of schizophrenia","volume":"4","author":"Yang","year":"2010","journal-title":"Front Hum Neurosci"},{"key":"2023011917143740100_ref12","first-page":"53","article-title":"Using multivariate machine learning methods and structural MRI to classify childhood onset schizophrenia and healthy controls","volume":"3","author":"Greenstein","year":"2012","journal-title":"Front Psych"},{"issue":"16","key":"2023011917143740100_ref13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-14-S4-S1","article-title":"Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes","volume":"14","author":"Wang","year":"2013","journal-title":"BMC Bioinformatics"},{"issue":"8","key":"2023011917143740100_ref14","doi-asserted-by":"crossref","first-page":"2561","DOI":"10.1093\/bioinformatics\/btz967","article-title":"Morbigenous brain region and gene detection with a genetically evolved random neural network cluster approach in late mild cognitive impairment","volume":"36","author":"Bi","year":"2020","journal-title":"Bioinformatics"},{"issue":"5","key":"2023011917143740100_ref15","doi-asserted-by":"crossref","first-page":"1252","DOI":"10.1109\/TMI.2016.2548501","article-title":"Automatic segmentation of MR brain images with a convolutional neural network","volume":"35","author":"Moeskops","year":"2016","journal-title":"IEEE Trans Med Imaging"},{"issue":"7697","key":"2023011917143740100_ref16","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1038\/nature25988","article-title":"Image reconstruction by domain-transform manifold learning","volume":"555","author":"Zhu","year":"2018","journal-title":"Nature"},{"key":"2023011917143740100_ref17","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.neuroimage.2017.07.059","article-title":"Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker","volume":"163","author":"Cole","year":"2017","journal-title":"Neuroimage"},{"key":"2023011917143740100_ref18","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1016\/j.scib.2019.05.008","article-title":"RESTplus: an improved toolkit for resting-state functional magnetic resonance imaging data processing","volume":"64","author":"Jia","year":"2019","journal-title":"Sci Bull"},{"key":"2023011917143740100_ref19","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1186\/s12864-020-6463-x","article-title":"How to study runs of homozygosity using PLINK? A guide for analyzing medium den-sity SNP data in livestock and pet species","volume":"21","author":"Meyermans","year":"2020","journal-title":"BMC Genomics"},{"issue":"10","key":"2023011917143740100_ref20","doi-asserted-by":"crossref","first-page":"2973","DOI":"10.1109\/JBHI.2020.2973324","article-title":"Multimodal data analysis of Alzheimer\u2019s disease based on clustering evolutionary random forest","volume":"24","author":"Bi","year":"2020","journal-title":"IEEE J Biomed Health Inform"},{"issue":"3","key":"2023011917143740100_ref21","doi-asserted-by":"crossref","first-page":"bbac093","DOI":"10.1093\/bib\/bbac093","article-title":"IHGC-GAN: influence hypergraph convolutional generative adversarial network for risk prediction of late mild cognitive impairment based on imaging genetic data","volume":"23","author":"Bi","year":"2022","journal-title":"Brief Bioinform"},{"issue":"1","key":"2023011917143740100_ref22","first-page":"1","article-title":"SWATH-MS analysis of cerebrospinal fluid to generate a robust battery of biomarkers for Alzheimer\u2019s disease","volume":"10","author":"Park","year":"2020","journal-title":"Sci Rep"},{"key":"2023011917143740100_ref23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neurobiolaging.2018.04.005","volume":"69","author":"Abdel-Hafiz","year":"2018","journal-title":"Neurobiol Aging"},{"issue":"1","key":"2023011917143740100_ref24","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1073\/pnas.2634794100","article-title":"Increased hippocampal neurogenesis in Alzheimer\u2019s disease","volume":"101","author":"Jin","year":"2004","journal-title":"Proc Natl Acad Sci"},{"key":"2023011917143740100_ref25","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2019.116459","article-title":"A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer\u2019s disease","volume":"208","author":"Liu","year":"2020","journal-title":"Neuroimage"},{"issue":"11","key":"2023011917143740100_ref26","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0206547","article-title":"Parahippocampal gyrus expression of endothelial and insulin receptor signaling pathway genes is modulated by Alzheimer\u2019s disease and normalized by treatment with anti-diabetic agents","volume":"13","author":"Katsel","year":"2018","journal-title":"PLoS One"},{"issue":"1","key":"2023011917143740100_ref27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-020-59327-2","article-title":"Fractional Anisotropy changes in parahippocampal cingulum due to Alzheimer\u2019s Disease","volume":"10","author":"Dalboni da Rocha","year":"2020","journal-title":"Sci Rep"},{"key":"2023011917143740100_ref28","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.neuroscience.2019.10.006","article-title":"The interaction between contactin and amyloid precursor protein and its role in Alzheimer\u2019s disease","volume":"424","author":"Bamford","year":"2020","journal-title":"Neuroscience"},{"issue":"7630","key":"2023011917143740100_ref29","doi-asserted-by":"crossref","first-page":"E4","DOI":"10.1038\/nature20129","article-title":"Ephrin Bs and canonical Reelin signalling","volume":"539","author":"Pohlkamp","year":"2016","journal-title":"Nature"},{"issue":"5","key":"2023011917143740100_ref30","doi-asserted-by":"crossref","first-page":"573","DOI":"10.2174\/156720511796391827","article-title":"The AICD interacting protein DAB1 is up-regulated in Alzheimer frontal cortex brain samples and causes deregulation of proteins involved in gene expression changes","volume":"8","author":"Muller","year":"2011","journal-title":"Curr Alzheimer Res"},{"key":"2023011917143740100_ref31","volume-title":"Lipid peroxidation and pathological disruption of the ApoE\/Reelin-ApoER2-DAB1 axis in sporadic Alzheimer\u2019s disease","author":"Ramsden","year":"2021"},{"key":"2023011917143740100_ref32","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.drugalcdep.2018.08.009","article-title":"Cigarette smoking is associated with cortical thinning in anterior frontal regions, insula and regions showing atrophy in early Alzheimer\u2019s Disease","volume":"192","author":"Durazzo","year":"2018","journal-title":"Drug Alcohol Depend"},{"key":"2023011917143740100_ref33","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/978-3-319-75468-0_19","volume-title":"Island of Reil (Insula) in the Human Brain","author":"Choi","year":"2018"},{"key":"2023011917143740100_ref34","doi-asserted-by":"crossref","first-page":"107","DOI":"10.3389\/fnagi.2020.00107","article-title":"Differences in cerebral structure associated with depressive symptoms in the elderly with Alzheimer\u2019s disease","volume":"12","author":"Wu","year":"2020","journal-title":"Front Aging Neurosci"},{"issue":"4","key":"2023011917143740100_ref35","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1093\/brain\/awaa068","article-title":"Medial temporal lobe connectivity and its associations with cognition in early Alzheimer\u2019s disease","volume":"143","author":"Berron","year":"2020","journal-title":"Brain"},{"issue":"6","key":"2023011917143740100_ref36","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1002\/alz.12079","article-title":"Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer\u2019s disease","volume":"16","author":"Flores","year":"2020","journal-title":"Alzheimer's Dementia"},{"issue":"3\u20134","key":"2023011917143740100_ref37","doi-asserted-by":"crossref","first-page":"207","DOI":"10.3233\/JAD-2000-23-403","volume":"2","author":"Grant","year":"2000","journal-title":"J Alzheimers Dis"},{"key":"2023011917143740100_ref38","doi-asserted-by":"crossref","first-page":"695479","DOI":"10.3389\/fncel.2021.695479","volume":"15","author":"Wang","year":"2021","journal-title":"Front Cell Neurosci"},{"issue":"9","key":"2023011917143740100_ref39","first-page":"2801","article-title":"Regulatory mechanism of microRNA-377 on CDH13 expression in the cell model of Alzheimer\u2019s disease","volume":"22","author":"Liu","year":"2018","journal-title":"Eur Rev Med Pharmacol Sci"},{"key":"2023011917143740100_ref40","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.patcog.2016.10.009","article-title":"Multi-modal classification of Alzheimer\u2019s disease using nonlinear graph fusion","volume":"63","author":"Tong","year":"2017","journal-title":"Pattern Recognit"},{"key":"2023011917143740100_ref41","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.media.2015.10.008","article-title":"A novel relational regularization feature selection method for joint regression and classification in AD diagnosis","volume":"38","author":"Zhu","year":"2017","journal-title":"Med Image Anal"},{"key":"2023011917143740100_ref42","article-title":"Multi-class Alzheimer disease classification using hybrid features","volume-title":"IEEE Future Technologies Conference","author":"Altaf","year":"2017"},{"key":"2023011917143740100_ref43","volume-title":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","author":"Li","year":"2017"},{"key":"2023011917143740100_ref44","volume-title":"2017 10th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)","author":"Cheng","year":"2017"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbac515\/48783238\/bbac515.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/1\/bbac515\/48783238\/bbac515.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T17:50:01Z","timestamp":1674150601000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac515\/6887308"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,11]]},"references-count":44,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1,19]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbac515","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,1]]},"published":{"date-parts":[[2022,12,11]]},"article-number":"bbac515"}}