{"title":"An approach to estimating protein networks of cell cycle based on least-squares methods for periodic signals","authors":"T. Azuma, Mayumi Ito, S. Adachi","doi":"10.1109/ICSENST.2011.6137021","DOIUrl":null,"url":null,"abstract":"This paper considers a least-squares method for state space models by using periodic signals and two theoretical properties of the least-squares method are shown. Moreover the least-squares method considered in this paper is applied to an estimation problem of protein networks for cell cycle in budding yeast. The derived properties of the least-squares method are verified in the estimation problem and the approach to estimate protein networks for cell cycle is demonstrated. Finally two mathematical models are derived based on the estimated protein network.","PeriodicalId":202062,"journal":{"name":"2011 Fifth International Conference on Sensing Technology","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Fifth International Conference on Sensing Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENST.2011.6137021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper considers a least-squares method for state space models by using periodic signals and two theoretical properties of the least-squares method are shown. Moreover the least-squares method considered in this paper is applied to an estimation problem of protein networks for cell cycle in budding yeast. The derived properties of the least-squares method are verified in the estimation problem and the approach to estimate protein networks for cell cycle is demonstrated. Finally two mathematical models are derived based on the estimated protein network.