{"title":"生物模型学习、设计与分析的自动化","authors":"Nataša Miškov-Živanov","doi":"10.1145/2742060.2743765","DOIUrl":null,"url":null,"abstract":"Although there have been several recent attempts to automate steps of the process of model development and analysis in cell signaling networks, closing the overall cycle between information extraction, model assembly and analysis, and design of questions to guide new information search and experiments still requires a significant amount of human intervention. In this paper, we give an overview of challenges in this process, and outline our approaches to tackle these challenges.","PeriodicalId":255133,"journal":{"name":"Proceedings of the 25th edition on Great Lakes Symposium on VLSI","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Automation of Biological Model Learning, Design and Analysis\",\"authors\":\"Nataša Miškov-Živanov\",\"doi\":\"10.1145/2742060.2743765\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although there have been several recent attempts to automate steps of the process of model development and analysis in cell signaling networks, closing the overall cycle between information extraction, model assembly and analysis, and design of questions to guide new information search and experiments still requires a significant amount of human intervention. In this paper, we give an overview of challenges in this process, and outline our approaches to tackle these challenges.\",\"PeriodicalId\":255133,\"journal\":{\"name\":\"Proceedings of the 25th edition on Great Lakes Symposium on VLSI\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th edition on Great Lakes Symposium on VLSI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2742060.2743765\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th edition on Great Lakes Symposium on VLSI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2742060.2743765","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automation of Biological Model Learning, Design and Analysis
Although there have been several recent attempts to automate steps of the process of model development and analysis in cell signaling networks, closing the overall cycle between information extraction, model assembly and analysis, and design of questions to guide new information search and experiments still requires a significant amount of human intervention. In this paper, we give an overview of challenges in this process, and outline our approaches to tackle these challenges.
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