{"title":"癌症转移的专家意见:从不确定性和差异中获取知识","authors":"A. Divoli","doi":"10.1109/CTS.2011.5928759","DOIUrl":null,"url":null,"abstract":"Research in computational biology is often contingent on principal notions. Mathematical modeling is relying on valid initial assumptions. Text mining algorithms can only retrieve or extract information found in text. Knowledge representation requires a degree of knowledge consensus. Our understanding of certain areas in biology, however, is still in its infancy having a ripple effect in computational efforts.","PeriodicalId":426543,"journal":{"name":"2011 International Conference on Collaboration Technologies and Systems (CTS)","volume":"310 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Expert opinions in cancer metastasis: Harvesting knowledge from uncertainty and discrepancies\",\"authors\":\"A. Divoli\",\"doi\":\"10.1109/CTS.2011.5928759\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Research in computational biology is often contingent on principal notions. Mathematical modeling is relying on valid initial assumptions. Text mining algorithms can only retrieve or extract information found in text. Knowledge representation requires a degree of knowledge consensus. Our understanding of certain areas in biology, however, is still in its infancy having a ripple effect in computational efforts.\",\"PeriodicalId\":426543,\"journal\":{\"name\":\"2011 International Conference on Collaboration Technologies and Systems (CTS)\",\"volume\":\"310 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Collaboration Technologies and Systems (CTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CTS.2011.5928759\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Collaboration Technologies and Systems (CTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CTS.2011.5928759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Expert opinions in cancer metastasis: Harvesting knowledge from uncertainty and discrepancies
Research in computational biology is often contingent on principal notions. Mathematical modeling is relying on valid initial assumptions. Text mining algorithms can only retrieve or extract information found in text. Knowledge representation requires a degree of knowledge consensus. Our understanding of certain areas in biology, however, is still in its infancy having a ripple effect in computational efforts.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
