{"title":"DNA序列分析复杂性测度的比较","authors":"Ricardo E. Monge, J. L. Crespo","doi":"10.1109/IWOBI.2014.6913941","DOIUrl":null,"url":null,"abstract":"This paper looks into DNA analysis by computing and comparing complexity measures, in addition to providing a review of recent studies regarding the measurement of DNA complexity. The authors compare Shannon Entropy, Kolmogorov Complexity (approximated by Lempel-Ziv Compressibility) and statistical complexity, and observe that regions corresponding to genes have consistently different complexity measures (i.e., they are more regular) than those regions that do not have any gene associated with them. This provides insight on how to develop new tools for automated DNA analysis.","PeriodicalId":433659,"journal":{"name":"3rd IEEE International Work-Conference on Bioinspired Intelligence","volume":"138 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Comparison of complexity measures for DNA sequence analysis\",\"authors\":\"Ricardo E. Monge, J. L. Crespo\",\"doi\":\"10.1109/IWOBI.2014.6913941\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper looks into DNA analysis by computing and comparing complexity measures, in addition to providing a review of recent studies regarding the measurement of DNA complexity. The authors compare Shannon Entropy, Kolmogorov Complexity (approximated by Lempel-Ziv Compressibility) and statistical complexity, and observe that regions corresponding to genes have consistently different complexity measures (i.e., they are more regular) than those regions that do not have any gene associated with them. This provides insight on how to develop new tools for automated DNA analysis.\",\"PeriodicalId\":433659,\"journal\":{\"name\":\"3rd IEEE International Work-Conference on Bioinspired Intelligence\",\"volume\":\"138 9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3rd IEEE International Work-Conference on Bioinspired Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWOBI.2014.6913941\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd IEEE International Work-Conference on Bioinspired Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWOBI.2014.6913941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of complexity measures for DNA sequence analysis
This paper looks into DNA analysis by computing and comparing complexity measures, in addition to providing a review of recent studies regarding the measurement of DNA complexity. The authors compare Shannon Entropy, Kolmogorov Complexity (approximated by Lempel-Ziv Compressibility) and statistical complexity, and observe that regions corresponding to genes have consistently different complexity measures (i.e., they are more regular) than those regions that do not have any gene associated with them. This provides insight on how to develop new tools for automated DNA analysis.
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