{"title":"An asymptotic-preserving scheme for systems of conservation laws with source terms on 2D unstructured meshes","authors":"Christophe Berthon,Guy Moebs,Céline Sarazin-Desbois,Rodolphe Turpault","doi":"10.2140/camcos.2016.11.55","DOIUrl":"https://doi.org/10.2140/camcos.2016.11.55","url":null,"abstract":"","PeriodicalId":49265,"journal":{"name":"Communications in Applied Mathematics and Computational Science","volume":"90 1","pages":"55-77"},"PeriodicalIF":2.1,"publicationDate":"2016-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-01-01DOI: 10.2140/camcos.2010.5.31
Wanda Strychalski, David Adalsteinsson, Timothy C Elston
Cells use signaling networks consisting of multiple interacting proteins to respond to changes in their environment. In many situations, such as chemotaxis, spatial and temporal information must be transmitted through the network. Recent computational studies have emphasized the importance of cellular geometry in signal transduction, but have been limited in their ability to accurately represent complex cell morphologies. We present a finite volume method that addresses this problem. Our method uses Cartesian cut cells and is second order in space and time. We use our method to simulate several models of signaling systems in realistic cell morphologies obtained from live cell images and examine the effects of geometry on signal transduction.
{"title":"A Cut Cell Method for Simulating Spatial Models of Biochemical Reaction Networks in Arbitrary Geometries.","authors":"Wanda Strychalski, David Adalsteinsson, Timothy C Elston","doi":"10.2140/camcos.2010.5.31","DOIUrl":"https://doi.org/10.2140/camcos.2010.5.31","url":null,"abstract":"<p><p>Cells use signaling networks consisting of multiple interacting proteins to respond to changes in their environment. In many situations, such as chemotaxis, spatial and temporal information must be transmitted through the network. Recent computational studies have emphasized the importance of cellular geometry in signal transduction, but have been limited in their ability to accurately represent complex cell morphologies. We present a finite volume method that addresses this problem. Our method uses Cartesian cut cells and is second order in space and time. We use our method to simulate several models of signaling systems in realistic cell morphologies obtained from live cell images and examine the effects of geometry on signal transduction.</p>","PeriodicalId":49265,"journal":{"name":"Communications in Applied Mathematics and Computational Science","volume":"5 1","pages":"31-53"},"PeriodicalIF":2.1,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2140/camcos.2010.5.31","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31834870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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