{"title":"[了解和预测病毒流行和进化的数据驱动研究]。","authors":"Jumpei Ito","doi":"10.2222/jsv.74.49","DOIUrl":null,"url":null,"abstract":"<p><p>The era of big data has begun in life sciences, and virology is no exception. Especially since COVID-19, virology has become one of the most genome data-rich fields in life sciences. In this article, I will introduce the new paradigm of \"understanding and predicting viral epidemics and evolution, \" made possible by the emergence of vast amounts of genome data, focusing on my research to date. Additionally, I would like to introduce our efforts toward advancing the field of viral informatics.</p>","PeriodicalId":75275,"journal":{"name":"Uirusu","volume":"74 1","pages":"49-56"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Data-Driven Research for Understanding and Predicting Viral Epidemics and Evolution].\",\"authors\":\"Jumpei Ito\",\"doi\":\"10.2222/jsv.74.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The era of big data has begun in life sciences, and virology is no exception. Especially since COVID-19, virology has become one of the most genome data-rich fields in life sciences. In this article, I will introduce the new paradigm of \\\"understanding and predicting viral epidemics and evolution, \\\" made possible by the emergence of vast amounts of genome data, focusing on my research to date. Additionally, I would like to introduce our efforts toward advancing the field of viral informatics.</p>\",\"PeriodicalId\":75275,\"journal\":{\"name\":\"Uirusu\",\"volume\":\"74 1\",\"pages\":\"49-56\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Uirusu\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2222/jsv.74.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Uirusu","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2222/jsv.74.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Data-Driven Research for Understanding and Predicting Viral Epidemics and Evolution].
The era of big data has begun in life sciences, and virology is no exception. Especially since COVID-19, virology has become one of the most genome data-rich fields in life sciences. In this article, I will introduce the new paradigm of "understanding and predicting viral epidemics and evolution, " made possible by the emergence of vast amounts of genome data, focusing on my research to date. Additionally, I would like to introduce our efforts toward advancing the field of viral informatics.