{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T08:14:25Z","timestamp":1772180065150,"version":"3.50.1"},"reference-count":158,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2022,3,12]],"date-time":"2022-03-12T00:00:00Z","timestamp":1647043200000},"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":["61702054"],"award-info":[{"award-number":["61702054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFA0706202"],"award-info":[{"award-number":["2019YFA0706202"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Identifying disease-related genes is an important issue in computational biology. Module structure widely exists in biomolecule networks, and complex diseases are usually thought to be caused by perturbations of local neighborhoods in the networks, which can provide useful insights for the study of disease-related genes. However, the mining and effective utilization of the module structure is still challenging in such issues as a disease gene prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We propose a hybrid disease-gene prediction method integrating multiscale module structure (HyMM), which can utilize multiscale information from local to global structure to more effectively predict disease-related genes. HyMM extracts module partitions from local to global scales by multiscale modularity optimization with exponential sampling, and estimates the disease relatedness of genes in partitions by the abundance of disease-related genes within modules. Then, a probabilistic model for integration of gene rankings is designed in order to integrate multiple predictions derived from multiscale module partitions and network propagation, and a parameter estimation strategy based on functional information is proposed to further enhance HyMM\u2019s predictive power. By a series of experiments, we reveal the importance of module partitions at different scales, and verify the stable and good performance of HyMM compared with eight other state-of-the-arts and its further performance improvement derived from the parameter estimation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The results confirm that HyMM is an effective framework for integrating multiscale module structure to enhance the ability to predict disease-related genes, which may provide useful insights for the study of the multiscale module structure and its application in such issues as a disease-gene prediction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bib\/bbac072","type":"journal-article","created":{"date-parts":[[2022,2,15]],"date-time":"2022-02-15T08:30:33Z","timestamp":1644913833000},"source":"Crossref","is-referenced-by-count":20,"title":["HyMM: hybrid method for disease-gene prediction by integrating multiscale module structure"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3045-5706","authenticated-orcid":false,"given":"Ju","family":"Xiang","sequence":"first","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, China; Department of Basic Medical Sciences & Academician Workstation, Changsha Medical University, Changsha, Hunan 410219, China"}]},{"given":"Xiangmao","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha 410083, China"}]},{"given":"Yichao","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4593-9332","authenticated-orcid":false,"given":"Fang-Xiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0188-1394","authenticated-orcid":false,"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, China"}]}],"member":"286","published-online":{"date-parts":[[2022,3,12]]},"reference":[{"key":"2022051813181144200_ref1","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1093\/bib\/bbp048","article-title":"Advances in translational bioinformatics: computational approaches for the hunting of disease genes","volume":"11","author":"Kann","year":"2010","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref2","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1093\/bfgp\/elr024","article-title":"Network-based methods for human disease gene prediction","volume":"10","author":"Wang","year":"2011","journal-title":"Brief Funct Genomics"},{"key":"2022051813181144200_ref3","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1038\/nrg3253","article-title":"Computational tools for prioritizing candidate genes: boosting disease gene discovery","volume":"13","author":"Moreau","year":"2012","journal-title":"Nat Rev Genet"},{"key":"2022051813181144200_ref4","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/nrg2918","article-title":"Network medicine: a network-based approach to human disease","volume":"12","author":"Barabasi","year":"2011","journal-title":"Nat Rev Genet"},{"key":"2022051813181144200_ref5","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1056\/NEJMp0808934","article-title":"Genomewide association studies\u2014illuminating biologic pathways","volume":"360","author":"Hirschhorn","year":"2009","journal-title":"N Engl J Med"},{"key":"2022051813181144200_ref6","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1038\/ng1090","article-title":"Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease","volume":"33","author":"Botstein","year":"2003","journal-title":"Nat Genet"},{"key":"2022051813181144200_ref7","doi-asserted-by":"crossref","first-page":"2098","DOI":"10.1093\/bib\/bby071","article-title":"Computational resources associating diseases with genotypes, phenotypes and exposures","volume":"20","author":"Zhang","year":"2019","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref8","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1093\/bib\/bbz038","article-title":"100 years of evolving gene\u2013disease complexities and scientific debutants","volume":"21","author":"Zeeshan","year":"2019","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/bib\/bbaa398","article-title":"Integrative bioinformatics and omics data source interoperability in the next-generation sequencing era\u2014editorial","volume":"22","author":"Rombo","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref10","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1093\/bib\/bbaa033","article-title":"GenoPheno: cataloging large-scale phenotypic and next-generation sequencing data within human datasets","volume":"22","author":"Guti\u00e9rrez-Sacrist\u00e1n","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref11","doi-asserted-by":"crossref","first-page":"270","DOI":"10.3389\/fgene.2019.00270","article-title":"Identifying disease-gene associations with graph-regularized manifold learning","volume":"10","author":"Luo","year":"2019","journal-title":"Front Genet"},{"key":"2022051813181144200_ref12","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1038\/s41467-019-08912-9","article-title":"Prioritizing Parkinson\u2019s disease genes using population-scale transcriptomic data","volume":"10","author":"Li","year":"2019","journal-title":"Nat Commun"},{"key":"2022051813181144200_ref13","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1016\/j.copbio.2010.07.010","article-title":"Diseases as network perturbations","volume":"21","author":"Sol","year":"2010","journal-title":"Curr Opin Biotechnol"},{"key":"2022051813181144200_ref14","first-page":"1370","article-title":"Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data","volume":"19","author":"Yan","year":"2017","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref15","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbaa303","article-title":"Recent advances in network-based methods for disease gene prediction","volume":"22","author":"Ata","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref16","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1093\/bib\/bbx151","article-title":"Systems bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches","volume":"20","author":"Oulas","year":"2017","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref17","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1093\/bib\/bbr075","article-title":"Network biology methods integrating biological data for translational science","volume":"13","author":"Bebek","year":"2012","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref18","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1093\/bib\/bbs043","article-title":"Network-based drug discovery by integrating systems biology and computational technologies","volume":"14","author":"Leung","year":"2012","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref19","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbab006","article-title":"Benchmarking network-based gene prioritization methods for cerebral small vessel disease","volume":"22","author":"Zhang","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref20","doi-asserted-by":"crossref","first-page":"100001","DOI":"10.1088\/1742-5468\/aae02b","article-title":"Predicting disease-related genes by path structure and community structure in protein\u2013protein networks","volume":"2018","author":"Hu","year":"2018","journal-title":"J Stat Mech Theory Exp"},{"key":"2022051813181144200_ref21","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1109\/TCBB.2016.2520947","article-title":"Prediction and validation of disease genes using HeteSim scores","volume":"14","author":"Zeng","year":"2017","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022051813181144200_ref22","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.jbi.2014.11.004","article-title":"Prioritization of potential candidate disease genes by topological similarity of protein\u2013protein interaction network and phenotype data","volume":"53","author":"Luo","year":"2015","journal-title":"J Biomed Inform"},{"key":"2022051813181144200_ref23","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1038\/nmeth.3484","article-title":"Phenolyzer: phenotype-based prioritization of candidate genes for human diseases","volume":"12","author":"Yang","year":"2015","journal-title":"Nat Methods"},{"key":"2022051813181144200_ref24","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1186\/s12864-016-3263-4","article-title":"Predicting disease-related genes using integrated biomedical networks","volume":"18","author":"Peng","year":"2017","journal-title":"BMC Genomics"},{"key":"2022051813181144200_ref25","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1016\/j.ins.2018.12.008","article-title":"Predicting disease-genes based on network information loss and protein complexes in heterogeneous network","volume":"479","author":"Lei","year":"2019","journal-title":"Inform Sci"},{"key":"2022051813181144200_ref26","doi-asserted-by":"crossref","first-page":"e1007078","DOI":"10.1371\/journal.pcbi.1007078","article-title":"Disease gene prediction for molecularly uncharacterized diseases","volume":"15","author":"C\u00e1ceres","year":"2019","journal-title":"PLoS Comput Biol"},{"key":"2022051813181144200_ref27","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1093\/bioinformatics\/bty637","article-title":"Random walk with restart on multiplex and heterogeneous biological networks","volume":"35","author":"Valdeolivas","year":"2018","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref28","doi-asserted-by":"crossref","first-page":"1536","DOI":"10.1093\/bioinformatics\/bty858","article-title":"Multimodal network diffusion predicts future disease\u2013gene\u2013chemical associations","volume":"35","author":"Lin","year":"2018","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref29","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1038\/s41467-020-14666-6","article-title":"Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder","volume":"11","author":"Dwivedi","year":"2020","journal-title":"Nat Commun"},{"key":"2022051813181144200_ref30","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1126\/science.1257601","article-title":"Uncovering disease-disease relationships through the incomplete interactome","volume":"347","author":"Menche","year":"2015","journal-title":"Science"},{"key":"2022051813181144200_ref31","doi-asserted-by":"crossref","first-page":"1240","DOI":"10.1038\/s41467-019-09177-y","article-title":"Network-based prediction of protein interactions","volume":"10","author":"Kov\u00e1cs","year":"2019","journal-title":"Nat Commun"},{"key":"2022051813181144200_ref32","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1007\/s00439-020-02253-0","article-title":"A network-based machine-learning framework to identify both functional modules and disease genes","volume":"140","author":"Yang","year":"2021","journal-title":"Hum Genet"},{"key":"2022051813181144200_ref33","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbaa353","article-title":"Pathogenic gene prediction based on network embedding","volume":"22","author":"Liu","year":"2021","journal-title":"Briefings in Bioinformatics"},{"key":"2022051813181144200_ref34","doi-asserted-by":"crossref","first-page":"bbab080","DOI":"10.1093\/bib\/bbab080","article-title":"NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction","volume":"22","author":"Xiang","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1399-0004.2006.00708.x","article-title":"The modular nature of genetic diseases","volume":"71","author":"Oti","year":"2007","journal-title":"Clin Genet"},{"key":"2022051813181144200_ref36","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1186\/s13073-014-0082-6","article-title":"Modules, networks and systems medicine for understanding disease and aiding diagnosis","volume":"6","author":"Gustafsson","year":"2014","journal-title":"Genome Med"},{"key":"2022051813181144200_ref37","doi-asserted-by":"crossref","first-page":"3005","DOI":"10.1093\/hmg\/ddv001","article-title":"A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma","volume":"24","author":"Sharma","year":"2015","journal-title":"Hum Mol Genet"},{"key":"2022051813181144200_ref38","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1038\/nbt1295","article-title":"A human phenome-interactome network of protein complexes implicated in genetic disorders","volume":"25","author":"Lage","year":"2007","journal-title":"Nat Biotechnol"},{"key":"2022051813181144200_ref39","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1073\/pnas.0605965104","article-title":"Resolution limit in community detection","volume":"104","author":"Fortunato","year":"2007","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2022051813181144200_ref40","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1016\/j.physa.2017.09.090","article-title":"Phase transition of surprise optimization in community detection","volume":"491","author":"Xiang","year":"2018","journal-title":"Phys A: Stat Mech Appl"},{"key":"2022051813181144200_ref41","doi-asserted-by":"crossref","first-page":"053213","DOI":"10.1088\/1742-5468\/aa6b2c","article-title":"Community detection based on significance optimization in complex networks","volume":"2017","author":"Xiang","year":"2017","journal-title":"J Stat Mech Theory Exp"},{"key":"2022051813181144200_ref42","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1038\/s41592-019-0509-5","article-title":"Assessment of network module identification across complex diseases","volume":"16","author":"Choobdar","year":"2019","journal-title":"Nat Methods"},{"key":"2022051813181144200_ref43","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1038\/nrg.2016.87","article-title":"Network biology concepts in complex disease comorbidities","volume":"17","author":"Hu","year":"2016","journal-title":"Nat Rev Genet"},{"key":"2022051813181144200_ref44","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.1016\/j.ajpath.2019.03.009","article-title":"Network medicine in pathobiology","volume":"189","author":"Lee","year":"2019","journal-title":"Am J Pathol"},{"key":"2022051813181144200_ref45","article-title":"A network-based method for brain disease gene prediction by integrating brain connectome and molecular network","volume":"23","author":"Wang","year":"2022","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2016.09.002","article-title":"Community detection in networks: a user guide","volume":"659","author":"Fortunato","year":"2016","journal-title":"Phys Rep"},{"key":"2022051813181144200_ref47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TKDE.2021.3104155","article-title":"A survey of community detection approaches: from statistical modeling to deep learning","author":"Jin","year":"2021","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2022051813181144200_ref48","doi-asserted-by":"crossref","first-page":"e1008239","DOI":"10.1371\/journal.pcbi.1008239","article-title":"Multiscale community detection in Cytoscape","volume":"16","author":"Singhal","year":"2020","journal-title":"PLoS Comput Biol"},{"key":"2022051813181144200_ref49","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbaa241","article-title":"DiSNEP: a disease-specific gene network enhancement to improve prioritizing candidate disease genes","volume":"22","author":"Ruan","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref50","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1093\/bib\/bbz091","article-title":"Heterogeneous information network and its application to human health and disease","volume":"21","author":"Ding","year":"2019","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref51","doi-asserted-by":"crossref","first-page":"bbab180","DOI":"10.1093\/bib\/bbab180","article-title":"A multiple network-based bioinformatics pipeline for the study of molecular mechanisms in oncological diseases for personalized medicine","volume":"22","author":"Dotolo","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref52","first-page":"575","article-title":"Gene co-expression analysis for functional classification and gene\u2013disease predictions","volume":"19","author":"Dam","year":"2018","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref53","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1016\/j.ajhg.2008.02.013","article-title":"Walking the Interactome for prioritization of candidate disease genes","volume":"82","author":"K\u00f6hler","year":"2008","journal-title":"Am J Hum Genet"},{"key":"2022051813181144200_ref54","doi-asserted-by":"crossref","first-page":"W305","DOI":"10.1093\/nar\/gkp427","article-title":"ToppGene suite for gene list enrichment analysis and candidate gene prioritization","volume":"37","author":"Chen","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2164-12-S3-S25","article-title":"Prioritizing disease candidate genes by a gene interconnectedness-based approach","volume":"12","author":"Hsu","year":"2011","journal-title":"BMC Genomics"},{"key":"2022051813181144200_ref56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1752-0509-6-S3-S8","article-title":"A vertex similarity-based framework to discover and rank orphan disease-related genes","volume":"6","author":"Zhu","year":"2012","journal-title":"BMC Syst Biol"},{"key":"2022051813181144200_ref57","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1093\/bioinformatics\/btq108","article-title":"Genome-wide inferring gene\u2013phenotype relationship by walking on the heterogeneous network","volume":"26","author":"Li","year":"2010","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref58","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1038\/msb.2008.27","article-title":"Network-based global inference of human disease genes","volume":"4","author":"Wu","year":"2008","journal-title":"Mol Syst Biol"},{"key":"2022051813181144200_ref59","doi-asserted-by":"crossref","first-page":"e0125138","DOI":"10.1371\/journal.pone.0125138","article-title":"Network-based phenome-genome association prediction by bi-random walk","volume":"10","author":"Xie","year":"2015","journal-title":"PLoS One"},{"key":"2022051813181144200_ref60","doi-asserted-by":"crossref","first-page":"e58977","DOI":"10.1371\/journal.pone.0058977","article-title":"Prediction and validation of gene-disease associations using methods inspired by social network analyses","volume":"8","author":"Singh-Blom","year":"2013","journal-title":"PLoS One"},{"key":"2022051813181144200_ref61","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.ymeth.2020.06.015","article-title":"PrGeFNE: predicting disease-related genes by fast network embedding","volume":"192","author":"Xiang","year":"2021","journal-title":"Methods"},{"key":"2022051813181144200_ref62","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1136\/amiajnl-2011-000658","article-title":"Identifying disease genes and module biomarkers by differential interactions","volume":"19","author":"Liu","year":"2012","journal-title":"J Am Med Inform Assoc"},{"key":"2022051813181144200_ref63","doi-asserted-by":"crossref","first-page":"35241","DOI":"10.1038\/srep35241","article-title":"Tissue specificity of human disease module","volume":"6","author":"Kitsak","year":"2016","journal-title":"Sci Rep"},{"key":"2022051813181144200_ref64","doi-asserted-by":"crossref","first-page":"61","DOI":"10.7150\/ijbs.7.61","article-title":"Prediction of human disease-related gene clusters by clustering analysis","volume":"7","author":"Sun","year":"2011","journal-title":"Int J Biol Sci"},{"key":"2022051813181144200_ref65","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1186\/s12864-017-4272-7","article-title":"Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome","volume":"18","author":"Akram","year":"2017","journal-title":"BMC Genomics"},{"key":"2022051813181144200_ref66","doi-asserted-by":"crossref","first-page":"578","DOI":"10.12688\/f1000research.10788.1","article-title":"Recent advances in predicting gene\u2013disease associations","volume":"6","author":"Opap","year":"2017","journal-title":"F1000Research"},{"key":"2022051813181144200_ref67","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s13721-017-0154-9","article-title":"Disease genes prioritizing mechanisms: a comprehensive and systematic literature review","volume":"6","author":"Seyyedrazzagi","year":"2017","journal-title":"Netw Model Anal Health Inform Bioinf"},{"key":"2022051813181144200_ref68","doi-asserted-by":"crossref","first-page":"e1383","DOI":"10.1002\/widm.1383","article-title":"Predicting disease-associated genes: computational methods, databases, and evaluations","volume":"11","author":"Luo","year":"2021","journal-title":"WIREs Data Mining and Knowledge Discovery"},{"key":"2022051813181144200_ref69","doi-asserted-by":"crossref","DOI":"10.1515\/jib-2018-0069","article-title":"A survey of gene prioritization tools for Mendelian and complex human diseases","volume":"16","author":"Zolotareva","year":"2019","journal-title":"J Integr Bioinform"},{"key":"2022051813181144200_ref70","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1038\/nrg.2017.38","article-title":"Network propagation: a universal amplifier of genetic associations","volume":"18","author":"Cowen","year":"2017","journal-title":"Nat Rev Genet"},{"key":"2022051813181144200_ref71","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1093\/jmcb\/mjv008","article-title":"Walking on multiple disease-gene networks to prioritize candidate genes","volume":"7","author":"Jiang","year":"2015","journal-title":"J Mol Cell Biol"},{"key":"2022051813181144200_ref72","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1093\/bib\/bbx029","article-title":"Context-based retrieval of functional modules in protein\u2013protein interaction networks","volume":"19","author":"Dobay","year":"2017","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref73","doi-asserted-by":"crossref","first-page":"bbab066","DOI":"10.1093\/bib\/bbab066","article-title":"On the limits of active module identification","volume":"22","author":"Lazareva","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref74","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1093\/bib\/bbt039","article-title":"Identifying protein complexes and functional modules\u2014from static PPI networks to dynamic PPI networks","volume":"15","author":"Chen","year":"2014","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref75","doi-asserted-by":"crossref","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","article-title":"Fast unfolding of communities in large networks","volume":"2008","author":"Blondel","year":"2008","journal-title":"J Stat Mech Theory Exp"},{"key":"2022051813181144200_ref76","doi-asserted-by":"crossref","first-page":"218701","DOI":"10.1103\/PhysRevLett.93.218701","article-title":"Detecting fuzzy community structures in complex networks with a Potts model","volume":"93","author":"Reichardt","year":"2004","journal-title":"Phys Rev Lett"},{"key":"2022051813181144200_ref77","doi-asserted-by":"crossref","first-page":"011047","DOI":"10.1103\/PhysRevX.4.011047","article-title":"Hierarchical block structures and high-resolution model selection in large networks","volume":"4","author":"Peixoto","year":"2014","journal-title":"Physical Review X"},{"key":"2022051813181144200_ref78","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/TKDE.2012.225","article-title":"Survey: functional module detection from protein-protein interaction networks","volume":"26","author":"Ji","year":"2014","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2022051813181144200_ref79","article-title":"Detecting protein complexes based on uncertain graph model","volume":"11","author":"Zhao","year":"2014","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022051813181144200_ref80","doi-asserted-by":"crossref","DOI":"10.1109\/TCBB.2021.3050102","article-title":"DPCMNE: detecting protein complexes from protein-protein interaction networks via multi-level network embedding","author":"Meng","year":"2021","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022051813181144200_ref81","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbz085","article-title":"A comprehensive review and evaluation of computational methods for identifying protein complexes from protein\u2013protein interaction networks","volume":"21","author":"Wu","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref82","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1038\/nrg1272","article-title":"Network biology: understanding the cell's functional organization","volume":"5","author":"Barabasi","year":"2004","journal-title":"Nat Rev Genet"},{"key":"2022051813181144200_ref83","first-page":"798","article-title":"Protein\u2013protein interactions: detection, reliability assessment and applications","volume":"18","author":"Peng","year":"2016","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref84","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1126\/science.1184819","article-title":"Community structure in time-dependent, multiscale, and multiplex networks","volume":"328","author":"Mucha","year":"2010","journal-title":"Science"},{"key":"2022051813181144200_ref85","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1038\/nature09182","article-title":"Link communities reveal multiscale complexity in networks","volume":"466","author":"Ahn","year":"2010","journal-title":"Nature"},{"key":"2022051813181144200_ref86","doi-asserted-by":"crossref","first-page":"053039","DOI":"10.1088\/1367-2630\/10\/5\/053039","article-title":"Analysis of the structure of complex networks at different resolution levels","volume":"10","author":"Arenas","year":"2008","journal-title":"New J Phys"},{"key":"2022051813181144200_ref87","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.physa.2015.03.006","article-title":"Multi-resolution community detection based on generalized self-loop rescaling strategy","volume":"432","author":"Xiang","year":"2015","journal-title":"Phys A: Stat Mech Appl"},{"key":"2022051813181144200_ref88","doi-asserted-by":"crossref","first-page":"033403","DOI":"10.1088\/1742-5468\/ab00eb","article-title":"Identifying multi-scale communities in networks by asymptotic surprise","volume":"2019","author":"Xiang","year":"2019","journal-title":"J Stat Mech Theory Exp"},{"key":"2022051813181144200_ref89","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1186\/1471-2105-6-39","article-title":"The use of edge-betweenness clustering to investigate biological function in protein interaction networks","volume":"6","author":"Dunn","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2022051813181144200_ref90","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1186\/1752-0509-4-100","article-title":"The function of communities in protein interaction networks at multiple scales","volume":"4","author":"Lewis","year":"2010","journal-title":"BMC Syst Biol"},{"key":"2022051813181144200_ref91","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1109\/TCBB.2010.75","article-title":"A fast hierarchical clustering algorithm for functional modules discovery in protein interaction networks","volume":"8","author":"Wang","year":"2011","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022051813181144200_ref92","doi-asserted-by":"crossref","first-page":"e1004120","DOI":"10.1371\/journal.pcbi.1004120","article-title":"A DIseAse MOdule detection (DIAMOnD) algorithm derived from a systematic analysis of connectivity patterns of disease proteins in the human Interactome","volume":"11","author":"Ghiassian","year":"2015","journal-title":"PLoS Comput Biol"},{"key":"2022051813181144200_ref93","article-title":"Online Mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders","volume":"33","author":"Hamosh","year":"2005","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref94","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.ymeth.2014.11.020","article-title":"DISEASES: text mining and data integration of disease\u2013gene associations","volume":"74","author":"Pletscher-Frankild","year":"2015","journal-title":"Methods"},{"key":"2022051813181144200_ref95","doi-asserted-by":"crossref","first-page":"D833","DOI":"10.1093\/nar\/gkw943","article-title":"DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants","volume":"45","author":"Pi\u00f1ero","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref96","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1093\/bib\/bbz064","article-title":"Genome-wide functional association networks: background, data & state-of-the-art resources","volume":"21","author":"Guala","year":"2019","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref97","first-page":"408","article-title":"Computational methods for discovering gene networks from expression data","volume":"10","author":"Lee","year":"2009","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref98","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1093\/bib\/bbp057","article-title":"Toward the dynamic interactome: it's about time","volume":"11","author":"Przytycka","year":"2010","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref99","doi-asserted-by":"crossref","first-page":"D548","DOI":"10.1093\/nar\/gkv1048","article-title":"SIGNOR: a database of causal relationships between biological entities","volume":"44","author":"Perfetto","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref100","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1093\/bib\/bbv059","article-title":"Computational analysis of protein interaction networks for infectious diseases","volume":"17","author":"Pan","year":"2016","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref101","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/bib\/bbr012","article-title":"Travelling the world of gene\u2013gene interactions","volume":"13","author":"Van Steen","year":"2011","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref102","doi-asserted-by":"crossref","first-page":"4212","DOI":"10.1038\/ncomms5212","article-title":"Human symptoms\u2013disease network","volume":"5","author":"Zhou","year":"2014","journal-title":"Nat Commun"},{"key":"2022051813181144200_ref103","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc Natl Acad Sci"},{"key":"2022051813181144200_ref104","first-page":"D330","article-title":"The gene ontology resource: 20 years and still going strong","volume":"47","author":"Consortium TGO","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref105","doi-asserted-by":"crossref","first-page":"D457","DOI":"10.1093\/nar\/gkv1070","article-title":"KEGG as a reference resource for gene and protein annotation","volume":"44","author":"Kanehisa","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref106","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkn863","article-title":"Reactome knowledgebase of human biological pathways and processes","volume":"37","author":"Matthews","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref107","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1109\/TCBB.2014.2361348","article-title":"ClusterViz: a Cytoscape APP for cluster analysis of biological network","volume":"12","author":"Wang","year":"2015","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022051813181144200_ref108","article-title":"Finding and evaluating community structure in networks","volume":"69","author":"Newman","year":"2004","journal-title":"Phys Rev E"},{"key":"2022051813181144200_ref109","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1140\/epjb\/e2012-30301-2","article-title":"Multi-resolution modularity methods and their limitations in community detection","volume":"85","author":"Xiang","year":"2012","journal-title":"European Physical Journal B"},{"key":"2022051813181144200_ref110","doi-asserted-by":"crossref","first-page":"4995","DOI":"10.1016\/j.physa.2012.05.006","article-title":"Limitation of multi-resolution methods in community detection","volume":"391","author":"Xiang","year":"2012","journal-title":"Phys A: Stat Mech Appl"},{"key":"2022051813181144200_ref111","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1093\/bioinformatics\/btu518","article-title":"Hybrid Bayesian-rank integration approach improves the predictive power of genomic dataset aggregation","volume":"31","author":"Badgeley","year":"2014","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref112","doi-asserted-by":"crossref","first-page":"1607","DOI":"10.1093\/bioinformatics\/btm158","article-title":"Weighted rank aggregation of cluster validation measures: a Monte Carlo cross-entropy approach","volume":"23","author":"Datta","year":"2007","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref113","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1093\/bioinformatics\/btr709","article-title":"Robust rank aggregation for gene list integration and meta-analysis","volume":"28","author":"Vilo","year":"2012","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref114","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1093\/bib\/bbx101","article-title":"A comparative study of rank aggregation methods for partial and top ranked lists in genomic applications","volume":"20","author":"Li","year":"2017","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref115","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1093\/bioinformatics\/btu684","article-title":"DOSE: an R\/Bioconductor package for disease ontology semantic and enrichment analysis","volume":"31","author":"Yu","year":"2015","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref116","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.3233\/JAD-141134","article-title":"Epidemiological and economic burden of Alzheimer's disease: a systematic literature review of data across Europe and the United States of America","volume":"43","author":"Takizawa","year":"2015","journal-title":"J Alzheimers Dis"},{"key":"2022051813181144200_ref117","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1186\/s13195-017-0297-z","article-title":"Alzheimer\u2019s disease prevention: from risk factors to early intervention","volume":"9","author":"Crous-Bou","year":"2017","journal-title":"Alzheimer's Res Ther"},{"key":"2022051813181144200_ref118","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1002\/ajmg.b.32499","article-title":"Genomic variants, genes, and pathways of Alzheimer's disease: an overview","volume":"174","author":"Naj","year":"2017","journal-title":"Am J Med Genet B Neuropsychiatr Genet"},{"key":"2022051813181144200_ref119","doi-asserted-by":"crossref","DOI":"10.1038\/s41380-020-01003-y","article-title":"Aberrant role of ALK in tau proteinopathy through autophagosomal dysregulation","volume":"26","author":"Park","year":"2021","journal-title":"Mol Psychiatry"},{"key":"2022051813181144200_ref120","doi-asserted-by":"crossref","first-page":"2734","DOI":"10.1038\/ncomms3734","article-title":"Lysosomal NEU1 deficiency affects amyloid precursor protein levels and amyloid-\u03b2 secretion via deregulated lysosomal exocytosis","volume":"4","author":"Annunziata","year":"2013","journal-title":"Nat Commun"},{"key":"2022051813181144200_ref121","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.neuron.2014.11.018","article-title":"NF\u03baB-activated astroglial release of complement C3 compromises neuronal morphology and function associated with Alzheimer's disease","volume":"85","author":"Lian","year":"2015","journal-title":"Neuron"},{"key":"2022051813181144200_ref122","doi-asserted-by":"crossref","first-page":"1589","DOI":"10.1016\/j.jalz.2018.07.223","article-title":"An updated Alzheimer hypothesis: complement C3 and risk of Alzheimer\u2018s disease\u2014a cohort study of 95,442 individuals","volume":"14","author":"Rasmussen","year":"2018","journal-title":"Alzheimers Dement"},{"key":"2022051813181144200_ref123","doi-asserted-by":"crossref","first-page":"303","DOI":"10.2174\/1567205013666161013091934","article-title":"Complement C4A and C4B gene copy number study in Alzheimer's disease patients","volume":"14","author":"Michele","year":"2017","journal-title":"Curr Alzheimer Res"},{"key":"2022051813181144200_ref124","doi-asserted-by":"crossref","DOI":"10.3389\/fnagi.2020.00017","article-title":"Adipose-derived molecules\u2013untouched horizons in Alzheimer's disease biology","volume":"12","author":"Pichiah","year":"2020","journal-title":"Front Aging Neurosci"},{"key":"2022051813181144200_ref125","doi-asserted-by":"crossref","first-page":"11883","DOI":"10.1096\/fj.201903128RR","article-title":"Alzheimer's disease in the gut\u2014major changes in the gut of 5xFAD model mice with ApoA1 as potential key player","volume":"34","author":"Stoye","year":"2020","journal-title":"FASEB J"},{"key":"2022051813181144200_ref126","doi-asserted-by":"crossref","first-page":"5559","DOI":"10.3390\/ijms22115559","article-title":"Ganoderic acid a promotes amyloid-\u03b2 clearance (in vitro) and ameliorates cognitive deficiency in Alzheimer\u2019s disease (mouse model) through autophagy induced by activating Axl","volume":"22","author":"Qi","year":"2021","journal-title":"Int J Mol Sci"},{"key":"2022051813181144200_ref127","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1007\/s12035-016-9722-8","article-title":"Methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and Alzheimer disease risk: a meta-analysis","volume":"54","author":"Rai","year":"2017","journal-title":"Mol Neurobiol"},{"key":"2022051813181144200_ref128","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1080\/15548627.2019.1633862","article-title":"MAPT\/tau accumulation represses autophagy flux by disrupting IST1-regulated ESCRT-III complex formation: a vicious cycle in Alzheimer neurodegeneration","volume":"16","author":"Feng","year":"2020","journal-title":"Autophagy"},{"key":"2022051813181144200_ref129","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1038\/ncb3409","article-title":"Turn up the lysosome","volume":"18","author":"Saftig","year":"2016","journal-title":"Nat Cell Biol"},{"key":"2022051813181144200_ref130","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s00401-015-1387-2","article-title":"Protein aggregation in Alzheimer\u2019s disease: A\u03b2 and \u03c4 and their potential roles in the pathogenesis of AD","volume":"129","author":"Thal","year":"2015","journal-title":"Acta Neuropathol"},{"key":"2022051813181144200_ref131","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1515\/revneuro-2014-0076","article-title":"Autophagy in Alzheimer\u2019s disease","volume":"26","author":"Zare-shahabadi","year":"2015","journal-title":"Rev Neurosci"},{"key":"2022051813181144200_ref132","doi-asserted-by":"crossref","first-page":"e1003012","DOI":"10.1371\/journal.pmed.1003012","article-title":"Dysregulation of multiple metabolic networks related to brain transmethylation and polyamine pathways in Alzheimer disease: a targeted metabolomic and transcriptomic study","volume":"17","author":"Mahajan","year":"2020","journal-title":"PLoS Med"},{"key":"2022051813181144200_ref133","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1016\/j.jalz.2017.01.020","article-title":"Metabolic network failures in Alzheimer's disease: a biochemical road map","volume":"13","author":"Toledo","year":"2017","journal-title":"Alzheimers Dement"},{"key":"2022051813181144200_ref134","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s100480050002","article-title":"Oxidative phosphorylation defects and Alzheimer's disease","volume":"1","author":"Shoffner","year":"1997","journal-title":"Neurogenetics"},{"key":"2022051813181144200_ref135","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1385\/NMM:5:2:147","article-title":"Differential expression of oxidative phosphorylation genes in patients with Alzheimer\u2019s disease","volume":"5","author":"Manczak","year":"2004","journal-title":"Neuromolecular Med"},{"key":"2022051813181144200_ref136","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1111\/jnc.13425","article-title":"Iron neurochemistry in Alzheimer's disease and Parkinson's disease: targets for therapeutics","volume":"139","author":"Belaidi","year":"2016","journal-title":"J Neurochem"},{"key":"2022051813181144200_ref137","doi-asserted-by":"crossref","first-page":"1255555","DOI":"10.1126\/science.1255555","article-title":"Neurodegeneration. Alzheimer's and Parkinson's diseases: the prion concept in relation to assembled A\u03b2, tau, and \u03b1-synuclein","volume":"349","author":"Goedert","year":"2015","journal-title":"Science"},{"key":"2022051813181144200_ref138","doi-asserted-by":"crossref","first-page":"eaag1166","DOI":"10.1126\/scitranslmed.aag1166","article-title":"The druggable genome and support for target identification and validation in drug development","volume":"9","author":"Finan","year":"2017","journal-title":"Sci Transl Med"},{"key":"2022051813181144200_ref139","first-page":"D1031","article-title":"Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics","volume":"48","author":"Wang","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref140","article-title":"Integration of the drug\u2013gene interaction database (DGIdb 4.0) with open crowdsource efforts","volume":"49","author":"Freshour","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2022051813181144200_ref141","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1126\/science.298.5594.824","article-title":"Network motifs: simple building blocks of complex networks","volume":"298","author":"Milo","year":"2002","journal-title":"Science"},{"key":"2022051813181144200_ref142","volume":"7","journal-title":"Bioinformatics"},{"key":"2022051813181144200_ref143","doi-asserted-by":"crossref","first-page":"bbaa068","DOI":"10.1093\/bib\/bbaa068","article-title":"Systematic evaluation of machine learning methods for identifying human\u2013pathogen protein\u2013protein interactions","volume":"22","author":"Chen","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref144","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbz170","article-title":"Deep learning-based clustering approaches for bioinformatics","volume":"22","author":"Karim","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref145","first-page":"325","article-title":"A review on machine learning principles for multi-view biological data integration","volume":"19","author":"Li","year":"2016","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref146","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1093\/bib\/bbaa032","article-title":"Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations","volume":"22","author":"Oh","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref147","article-title":"Advances in bulk and single-cell multi-omics approaches for systems biology and precision medicine","volume":"22","author":"Li","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref148","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1093\/bib\/bbaa121","article-title":"Comparison of microbiome samples: methods and computational challenges","volume":"22","author":"Comin","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref149","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1093\/bib\/bbaa101","article-title":"Epidemiological data analysis of viral quasispecies in the next-generation sequencing era","volume":"22","author":"Knyazev","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref150","doi-asserted-by":"crossref","first-page":"628","DOI":"10.1093\/bib\/bbv108","article-title":"Dimension reduction techniques for the integrative analysis of multi-omics data","volume":"17","author":"Meng","year":"2016","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref151","doi-asserted-by":"crossref","first-page":"333","DOI":"10.26599\/TST.2021.9010006","article-title":"Secure scheme for locating disease-causing genes based on multi-key homomorphic encryption","volume":"27","author":"Zhou","year":"2022","journal-title":"Tsinghua Sci Technol"},{"key":"2022051813181144200_ref152","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1093\/bib\/bbaa122","article-title":"Structured sparsity regularization for analyzing high-dimensional omics data","volume":"22","author":"Vinga","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref153","doi-asserted-by":"crossref","first-page":"58","DOI":"10.26599\/TST.2021.9010003","article-title":"Metabolite-disease association prediction algorithm combining DeepWalk and random forest","volume":"27","author":"Tie","year":"2022","journal-title":"Tsinghua Sci Technol"},{"key":"2022051813181144200_ref154","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1093\/bib\/bbz146","article-title":"Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when","volume":"22","author":"Galano-Frutos","year":"2019","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref155","doi-asserted-by":"crossref","first-page":"280","DOI":"10.26599\/BDMA.2020.9020025","article-title":"CircRNA-disease associations prediction based on metapath2vec++ and matrix factorization","volume":"3","author":"Zhang","year":"2020","journal-title":"Big Data Mining and Analytics"},{"key":"2022051813181144200_ref156","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1093\/bib\/bbaa100","article-title":"Using conceptual modeling to improve genome data management","volume":"22","author":"Pastor","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref157","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1093\/bib\/bbaa080","article-title":"The road towards data integration in human genomics: players, steps and interactions","volume":"22","author":"Bernasconi","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022051813181144200_ref158","article-title":"Computational methods for the integrative analysis of single-cell data","volume":"22","author":"Forcato","year":"2020","journal-title":"Brief Bioinform"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/3\/bbac072\/43745640\/bbac072.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/3\/bbac072\/43745640\/bbac072.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T09:28:39Z","timestamp":1700213319000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac072\/6547263"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,12]]},"references-count":158,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,5,13]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbac072","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.04.30.442111","asserted-by":"object"}]},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,5]]},"published":{"date-parts":[[2022,3,12]]},"article-number":"bbac072"}}