Christopher R. Reynolds, Kealan Exley, Matthieu A. Bultelle, Inaki Sainz de Murieta, Richard I. Kitney
{"title":"通过时程事件序列分析调试实验机械","authors":"Christopher R. Reynolds, Kealan Exley, Matthieu A. Bultelle, Inaki Sainz de Murieta, Richard I. Kitney","doi":"10.1049/enb.2017.0008","DOIUrl":null,"url":null,"abstract":"<div>\n <p>This application note describes an open-source web application software package for viewing and analysing time-course event sequences in the form of log files containing timestamps. Web pages allow the visualisation of time-course event sequences as time curves and the comparison of sequences against each other to visualise deviations between the timings of the sequences. A feature allows the analysis of the sequences by parsing selected sections with a support vector machine model that heuristically calculates a value for the likelihood of an error occurring based on the textual output in the log files. This allows quick analysis for errors in files with large numbers of log events. The software is written in ASP.NET with Visual Basic code-behind to allow it to be hosted on servers and integrated into web application frameworks.</p>\n </div>","PeriodicalId":72921,"journal":{"name":"Engineering biology","volume":"1 1","pages":"51-54"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1049/enb.2017.0008","citationCount":"1","resultStr":"{\"title\":\"Debugging experiment machinery through time-course event sequence analysis\",\"authors\":\"Christopher R. Reynolds, Kealan Exley, Matthieu A. Bultelle, Inaki Sainz de Murieta, Richard I. Kitney\",\"doi\":\"10.1049/enb.2017.0008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p>This application note describes an open-source web application software package for viewing and analysing time-course event sequences in the form of log files containing timestamps. Web pages allow the visualisation of time-course event sequences as time curves and the comparison of sequences against each other to visualise deviations between the timings of the sequences. A feature allows the analysis of the sequences by parsing selected sections with a support vector machine model that heuristically calculates a value for the likelihood of an error occurring based on the textual output in the log files. This allows quick analysis for errors in files with large numbers of log events. The software is written in ASP.NET with Visual Basic code-behind to allow it to be hosted on servers and integrated into web application frameworks.</p>\\n </div>\",\"PeriodicalId\":72921,\"journal\":{\"name\":\"Engineering biology\",\"volume\":\"1 1\",\"pages\":\"51-54\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1049/enb.2017.0008\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/enb.2017.0008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering biology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/enb.2017.0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Debugging experiment machinery through time-course event sequence analysis
This application note describes an open-source web application software package for viewing and analysing time-course event sequences in the form of log files containing timestamps. Web pages allow the visualisation of time-course event sequences as time curves and the comparison of sequences against each other to visualise deviations between the timings of the sequences. A feature allows the analysis of the sequences by parsing selected sections with a support vector machine model that heuristically calculates a value for the likelihood of an error occurring based on the textual output in the log files. This allows quick analysis for errors in files with large numbers of log events. The software is written in ASP.NET with Visual Basic code-behind to allow it to be hosted on servers and integrated into web application frameworks.