{"title":"2003-2018年《基因组学与信息学》与其他生物信息学驱动期刊的期刊距离估算。","authors":"Ji-Hye Oh, Hee-Jo Nam, Hyun-Seok Park","doi":"10.5808/gi.21074","DOIUrl":null,"url":null,"abstract":"<p><p>This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).</p>","PeriodicalId":36591,"journal":{"name":"Genomics and Informatics","volume":"19 4","pages":"e51"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8752985/pdf/","citationCount":"0","resultStr":"{\"title\":\"Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003-2018.\",\"authors\":\"Ji-Hye Oh, Hee-Jo Nam, Hyun-Seok Park\",\"doi\":\"10.5808/gi.21074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).</p>\",\"PeriodicalId\":36591,\"journal\":{\"name\":\"Genomics and Informatics\",\"volume\":\"19 4\",\"pages\":\"e51\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8752985/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genomics and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5808/gi.21074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/12/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genomics and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5808/gi.21074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/12/31 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003-2018.
This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).
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