{"title":"计算生物学:从15到0的生物学洞察力","authors":"Harold R Garner , Alexander Pertsemlidis","doi":"10.1016/S1478-5382(03)02260-1","DOIUrl":null,"url":null,"abstract":"<div><p>There is no doubt that both computational biology and bioinformatics, and the interface of computer science and biology in general, are central to the future of biological research. The disciplines span a process that begins with data collection, analysis, classification, and integration and ends with interpretation, modeling, visualization, and prediction. Data mining may play a role in the middle, depending on the size of the dataset. Overall, the focus is on identifying opportunities and developing computational solutions (including algorithms, models, tools, and databases) that can be used for experimental design, data analysis and interpretation and hypothesis generation. The fundamental challenges are to describe, analyze, simulate and predict the dynamics of life processes.</p></div>","PeriodicalId":9227,"journal":{"name":"Biosilico","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2003-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02260-1","citationCount":"4","resultStr":"{\"title\":\"Computational biology: biological insight from 1s and 0s\",\"authors\":\"Harold R Garner , Alexander Pertsemlidis\",\"doi\":\"10.1016/S1478-5382(03)02260-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>There is no doubt that both computational biology and bioinformatics, and the interface of computer science and biology in general, are central to the future of biological research. The disciplines span a process that begins with data collection, analysis, classification, and integration and ends with interpretation, modeling, visualization, and prediction. Data mining may play a role in the middle, depending on the size of the dataset. Overall, the focus is on identifying opportunities and developing computational solutions (including algorithms, models, tools, and databases) that can be used for experimental design, data analysis and interpretation and hypothesis generation. The fundamental challenges are to describe, analyze, simulate and predict the dynamics of life processes.</p></div>\",\"PeriodicalId\":9227,\"journal\":{\"name\":\"Biosilico\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S1478-5382(03)02260-1\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biosilico\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1478538203022601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosilico","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1478538203022601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computational biology: biological insight from 1s and 0s
There is no doubt that both computational biology and bioinformatics, and the interface of computer science and biology in general, are central to the future of biological research. The disciplines span a process that begins with data collection, analysis, classification, and integration and ends with interpretation, modeling, visualization, and prediction. Data mining may play a role in the middle, depending on the size of the dataset. Overall, the focus is on identifying opportunities and developing computational solutions (including algorithms, models, tools, and databases) that can be used for experimental design, data analysis and interpretation and hypothesis generation. The fundamental challenges are to describe, analyze, simulate and predict the dynamics of life processes.