{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T13:26:35Z","timestamp":1781616395617,"version":"3.54.5"},"reference-count":50,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T00:00:00Z","timestamp":1700006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2022YFF1203202"],"award-info":[{"award-number":["2022YFF1203202"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2018YFC2000205"],"award-info":[{"award-number":["2018YFC2000205"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["XDB38050200"],"award-info":[{"award-number":["XDB38050200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["XDA26040304"],"award-info":[{"award-number":["XDA26040304"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["SRPG22-007"],"award-info":[{"award-number":["SRPG22-007"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["2022YFF1203202"],"award-info":[{"award-number":["2022YFF1203202"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["2018YFC2000205"],"award-info":[{"award-number":["2018YFC2000205"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDB38050200"],"award-info":[{"award-number":["XDB38050200"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA26040304"],"award-info":[{"award-number":["XDA26040304"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["SRPG22-007"],"award-info":[{"award-number":["SRPG22-007"]}]},{"name":"Self-supporting Program of Guangzhou Laboratory","award":["2022YFF1203202"],"award-info":[{"award-number":["2022YFF1203202"]}]},{"name":"Self-supporting Program of Guangzhou Laboratory","award":["2018YFC2000205"],"award-info":[{"award-number":["2018YFC2000205"]}]},{"name":"Self-supporting Program of Guangzhou Laboratory","award":["XDB38050200"],"award-info":[{"award-number":["XDB38050200"]}]},{"name":"Self-supporting Program of Guangzhou Laboratory","award":["XDA26040304"],"award-info":[{"award-number":["XDA26040304"]}]},{"name":"Self-supporting Program of Guangzhou Laboratory","award":["SRPG22-007"],"award-info":[{"award-number":["SRPG22-007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Microorganisms"],"abstract":"<jats:p>Since COVID-19 has brought great challenges to global public health governance, developing methods that track the evolution of the virus over the course of an epidemic or pandemic is useful for public health. This paper uses anomaly detection models to analyze SARS-CoV-2 virus genome k-mers to predict possible new critical variants in the collected samples. We used the sample data from Argentina, China and Portugal obtained from the Global Initiative on Sharing All Influenza Data (GISAID) to conduct multiple rounds of evaluation on several anomaly detection models, to verify the feasibility of this virus early warning and surveillance idea and find appropriate anomaly detection models for actual epidemic surveillance. Through multiple rounds of model testing, we found that the LUNAR (learnable unified neighborhood-based anomaly ranking) and LUNAR+LUNAR stacking model performed well in new critical variants detection. The results of simulated dynamic detection validate the feasibility of this approach, which can help efficiently monitor samples in local areas.<\/jats:p>","DOI":"10.3390\/microorganisms11112773","type":"journal-article","created":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T00:47:48Z","timestamp":1700009268000},"page":"2773","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Anomaly Detection Models for SARS-CoV-2 Surveillance Based on Genome k-mers"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5261-5651","authenticated-orcid":false,"given":"Haotian","family":"Ren","sequence":"first","affiliation":[{"name":"Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yixue","family":"Li","sequence":"additional","affiliation":[{"name":"Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China"},{"name":"Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China"},{"name":"Guangzhou Laboratory, Guangzhou 510005, China"},{"name":"School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China"},{"name":"Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1975-9693","authenticated-orcid":false,"given":"Tao","family":"Huang","sequence":"additional","affiliation":[{"name":"Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,15]]},"reference":[{"key":"ref_1","first-page":"100116","article-title":"Genomic Variation, Origin Tracing, and Vaccine Development of SARS-CoV-2: A Systematic Review","volume":"2","author":"Li","year":"2021","journal-title":"Innovation"},{"key":"ref_2","unstructured":"WHO (2023, May 08). Tracking SARS-CoV-2 Variants. Available online: https:\/\/www.who.int\/en\/activities\/tracking-SARS-CoV-2-variants\/."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.12998\/wjcc.v10.i1.1","article-title":"Omicron Variant (B.1.1.529) of SARS-CoV-2: Mutation, Infectivity, Transmission, and Vaccine Resistance","volume":"10","author":"Ren","year":"2022","journal-title":"World J. Clin. Cases"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"102246","DOI":"10.1016\/j.tmaid.2021.102246","article-title":"The Emergence of New SARS-CoV-2 Variant (Omicron) and Increasing Calls for COVID-19 vaccine boosters-The debate continues","volume":"45","author":"Khan","year":"2022","journal-title":"Travel Med. Infect. Dis."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e2106","DOI":"10.1002\/rmv.2106","article-title":"Laboratory testing of SARS-CoV, MERS-CoV, and SARS-CoV-2 (2019-nCoV): Current Status, Challenges, and Countermeasures","volume":"30","author":"Yan","year":"2020","journal-title":"Rev. Med. Virol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12879-022-07374-7","article-title":"Identification of SARS-CoV-2 Variants Using Viral Sequencing for the Centers for Disease Control and Prevention Genomic Surveillance Program","volume":"22","author":"Goswami","year":"2022","journal-title":"BMC Infect. Dis."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Berno, G., Fabeni, L., Matusali, G., Gruber, C.E.M., Rueca, M., Giombini, E., and Garbuglia, A.R. (2022). SARS-CoV-2 Variants Identification: Overview of Molecular Existing Methods. Pathogens, 11.","DOI":"10.3390\/pathogens11091058"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Caputo, E., and Mandrich, L. (2022). Structural and Phylogenetic Analysis of SARS-CoV-2 Spike Glycoprotein from the Most Widespread Variants. Life, 12.","DOI":"10.3390\/life12081245"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ren, H., Ling, Y., Cao, R., Wang, Z., Li, Y., and Huang, T. (2023). Early Warning of Emerging Infectious Diseases Based on Multimodal Data. Biosaf. Health, online ahead of print.","DOI":"10.1016\/j.bsheal.2023.05.006"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chao, J.N., Tang, F.R., and Xu, L. (2022). Developments in Algorithms for Sequence Alignment: A Review. Biomolecules, 12.","DOI":"10.3390\/biom12040546"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1038\/s41586-020-2012-7","article-title":"A Pneumonia Outbreak Associated with a New Coronavirus of Probable Bat Origin","volume":"579","author":"Zhou","year":"2020","journal-title":"Nature"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1093\/bib\/bbv099","article-title":"Multiple Sequence Alignment Modeling: Methods and Applications","volume":"17","author":"Chatzou","year":"2016","journal-title":"Brief. Bioinform."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1186\/s13059-017-1319-7","article-title":"Alignment-Free Sequence Comparison: Benefits, Applications, and Tools","volume":"18","author":"Zielezinski","year":"2017","journal-title":"Genome Biol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1038\/s41588-021-00862-7","article-title":"Ultrafast Sample placement on Existing tRees (UShER) Enables Real-Time Phylogenetics for the SARS-CoV-2 Pandemic","volume":"53","author":"Turakhia","year":"2021","journal-title":"Nat. Genet."},{"key":"ref_15","first-page":"239","article-title":"Success of Alignment-Free Oligonucleotide (k-mer) Analysis Confirms Relative Importance of Genomes not Genes in Speciation and Phylogeny","volume":"128","author":"Forsdyke","year":"2019","journal-title":"Biol. J. Linn. Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.gene.2018.12.040","article-title":"Alignment-Free Approaches for Predicting Novel Nuclear Mitochondrial Segments (NUMTs) in the Human Genome","volume":"691","author":"Li","year":"2019","journal-title":"Gene"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ma, Y.L., Yu, Z.G., Tang, R.B., Xie, X.H., Han, G.H., and Anh, V.V. (2020). Phylogenetic Analysis of HIV-1 Genomes Based on the Position-Weighted K-mers Method. Entropy, 22.","DOI":"10.3390\/e22020255"},{"key":"ref_18","first-page":"208","article-title":"Iterative Spaced Seed Hashing: Closing the Gap Between Spaced Seed Hashing and k-mer Hashing","volume":"11490","author":"Petrucci","year":"2019","journal-title":"Bioinform. Res. Appl. Isbra"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40168-017-0283-5","article-title":"VirFinder: A Novel k-mer Based Tool for Identifying Viral Sequences from Assembled Metagenomic Data","volume":"5","author":"Ren","year":"2017","journal-title":"Microbiome"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"W554","DOI":"10.1093\/nar\/gkx351","article-title":"CAFE: Accelerated Alignment-FrEe Sequence Analysis","volume":"45","author":"Lu","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1089\/cmb.2021.0536","article-title":"kmer2vec: A Novel Method for Comparing DNA Sequences by word2vec Embedding","volume":"29","author":"Ren","year":"2022","journal-title":"J. Comput. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"107662","DOI":"10.1016\/j.ympev.2022.107662","article-title":"KINN: An Alignment-Free Accurate Phylogeny Reconstruction Method Based on Inner Distance Distributions of k-mer Pairs in Biological Sequences","volume":"179","author":"Tang","year":"2023","journal-title":"Mol. Phylogenet Evol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.jtbi.2014.08.028","article-title":"k-mer Sparse Matrix Model for Genetic Sequence and Its Applications in Sequence Comparison","volume":"363","author":"Wen","year":"2014","journal-title":"J. Theor. Biol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"78658","DOI":"10.1109\/ACCESS.2021.3083060","article-title":"Machine Learning for Anomaly Detection: A Systematic Review","volume":"9","author":"Nassif","year":"2021","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e1280","DOI":"10.1002\/widm.1280","article-title":"There and Back Again: Outlier Detection between Statistical Reasoning and Data Mining Algorithms","volume":"8","author":"Zimek","year":"2018","journal-title":"Wires Data Min. Knowl."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.sigpro.2013.12.026","article-title":"A Review of Novelty Detection","volume":"99","author":"Pimentel","year":"2014","journal-title":"Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1541880.1541882","article-title":"Anomaly Detection: A survey","volume":"41","author":"Chandola","year":"2009","journal-title":"ACM Comput. Surv."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3439950","article-title":"Deep Learning for Anomaly Detection: A Review","volume":"54","author":"Pang","year":"2021","journal-title":"ACM Comput. Surv."},{"key":"ref_29","first-page":"1","article-title":"PyOD: A Python Toolbox for Scalable Outlier Detection","volume":"20","author":"Zhao","year":"2019","journal-title":"Comput. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"12181","DOI":"10.1109\/TKDE.2022.3159580","article-title":"ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions","volume":"35","author":"Li","year":"2022","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_31","unstructured":"Sch\u00f6lkopf, B., Williamson, R., Smola, A., Shawe-Taylor, J., and Platt, J. (December, January 29). Support Vector Method for Novelty Detection. Proceedings of the 12th International Conference on Neural Information Processing Systems, Denver, CO, USA."},{"key":"ref_32","unstructured":"Angiulli, F., and Pizzuti, C. (2002). Principles of Data Mining and Knowledge Discovery, Springer."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2133360.2133363","article-title":"Isolation-Based Anomaly Detection","volume":"6","author":"Liu","year":"2012","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Michelucci, U. (2022). Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python, Apress.","DOI":"10.1007\/978-1-4842-8020-1"},{"key":"ref_35","first-page":"6737","article-title":"LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks","volume":"36","author":"Goodge","year":"2022","journal-title":"AAAI Conf. Artif. Intell."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhang, Y.Z., Liu, J.J., and Shen, W.J. (2022). A Review of Ensemble Learning Algorithms Used in Remote Sensing Applications. Appl. Sci., 12.","DOI":"10.3390\/app12178654"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1007\/s10994-019-05855-6","article-title":"A Survey on Semi-Supervised Learning","volume":"109","author":"Hoos","year":"2020","journal-title":"Mach. Learn."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"e100643","DOI":"10.1136\/bmjhci-2022-100643","article-title":"Predicting Emerging SARS-CoV-2 Variants of Concern through a One Class Dynamic Anomaly Detection Algorithm","volume":"29","author":"Nicora","year":"2022","journal-title":"BMJ Health Care Inform."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1002\/gch2.1018","article-title":"Data, Disease and Diplomacy: GISAID\u2019s Innovative Contribution to Global Health","volume":"1","author":"Elbe","year":"2017","journal-title":"Glob. Chall."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Taskforce for Joint Prevention and Control Mechanism for COVID-19 under the State Council and the National Health Commission of P.R. China (2023). Scientific and Targeted Prevention and Control Measures to Optimize COVID-19 Response. Health Care Sci., 2, 1\u20136.","DOI":"10.1002\/hcs2.33"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"495","DOI":"10.3389\/fpubh.2020.00495","article-title":"On the Progression of COVID-19 in Portugal: A Comparative Analysis of Active Cases Using Non-linear Regression","volume":"8","author":"Milhinhos","year":"2020","journal-title":"Front. Public. Health"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2252","DOI":"10.1002\/jmv.26659","article-title":"SARS-CoV-2 in Argentina: Lockdown, Mobility, and Contagion","volume":"93","author":"Larrosa","year":"2021","journal-title":"J. Med. Virol."},{"key":"ref_43","unstructured":"(2023, October 21). Data, Our World in \u201cCoronavirus (COVID-19)\u201d Vaccinations. Available online: https:\/\/ourworldindata.org\/covid-vaccinations."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4121","DOI":"10.1093\/bioinformatics\/bty407","article-title":"Nextstrain: Real-Time Tracking of Pathogen Evolution","volume":"34","author":"Hadfield","year":"2018","journal-title":"Bioinformatics"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Chicco, D., and Jurman, G. (2020). The Advantages of the Matthews Correlation Coefficient (MCC) over F1 Score and Accuracy in Binary Classification Evaluation. BMC Genom., 21.","DOI":"10.1186\/s12864-019-6413-7"},{"key":"ref_46","first-page":"97","article-title":"An Introduction to the Bootstrap","volume":"63","author":"Markus","year":"1998","journal-title":"Psychometrika"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1016\/j.it.2020.10.004","article-title":"Mechanisms of SARS-CoV-2 Transmission and Pathogenesis","volume":"41","author":"Harrison","year":"2020","journal-title":"Trends Immunol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1111\/j.1750-2659.2009.00077.x","article-title":"Seasonal and Pandemic Influenza Surveillance Considerations for Constructing Multicomponent Systems","volume":"3","author":"Brammer","year":"2009","journal-title":"Influenza Other Respir. Viruses"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Bonidia, R.P., Domingues, D.S., Sanches, D.S., and de Carvalho, A. (2022). MathFeature: Feature Extraction Package for DNA, RNA and Protein Sequences Based on Mathematical Descriptors. Brief. Bioinform., 23.","DOI":"10.1093\/bib\/bbab434"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Tan, C.H., Lee, V.C., and Salehi, M. (2020, January 17\u201320). MIR_MAD: An Efficient and On-line Approach for Anomaly Detection in Dynamic Data Stream. Proceedings of the 20th IEEE International Conference on Data Mining (ICDM), Electr Network, Sorrento, Italy.","DOI":"10.1109\/ICDMW51313.2020.00065"}],"container-title":["Microorganisms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-2607\/11\/11\/2773\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:23:10Z","timestamp":1760131390000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-2607\/11\/11\/2773"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,15]]},"references-count":50,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["microorganisms11112773"],"URL":"https:\/\/doi.org\/10.3390\/microorganisms11112773","relation":{},"ISSN":["2076-2607"],"issn-type":[{"value":"2076-2607","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,15]]}}}