Beatbox - A Computer Simulation Environment for Computational Biology of the Heart

Ross McFarlane, I. Biktasheva
{"title":"Beatbox - A Computer Simulation Environment for Computational Biology of the Heart","authors":"Ross McFarlane, I. Biktasheva","doi":"10.14236/EWIC/VOCS2008.10","DOIUrl":null,"url":null,"abstract":"Despite over a century's study, the trigger mechanisms of cardiac arrhythmias are poorly understood. Even modern experimental methods do not provide sufficient temporal and spacial resolution to trace the development of fibrillation in samples of cardiac tissue, not to mention the heart in vivo. Advances in human genetics provide information on the impact of certain genes on cellular activity, but do not explain the resultant mechanisms by which fibrillation arises. Thus, for some genetic cardiac diseases, the first presenting symptom is death. \n \nComputer simulations of electrical activity in cardiac tissue offer increasingly detailed insight into these phenomena, providing a view of cellular-level activity on the scale of a whole tissue wall. Already, advances in this field have led to developments in our understanding of heart fibrillation and sudden cardiac death and their impact is expected to increase significantly as we approach the ultimate goal of whole-heart modelling. \n \nModelling the propagation of Action Potential through cardiac tissue is computationally expensive due to the huge number of equations per cell and the vast spacial and temporal scales required. The complexity of the problem encompasses the description of ionic currents underlying excitation of a single cell through the inhomogeneity of the tissue to the complex geometry of the whole heart. The timely running of computational models of cardiac tissue is increasingly dependant on the effective use of High Performance Computing (HPC), i.e. systems with parallel processors. Current state of the art cardiac simulation tools are limited either by the availability of modern, detailed models, or by their hardware portability or ease of use. The miscellany of current model implementations leads many researchers to develop their own ad-hoc software, preventing them from both utilising the power of HPC effectively, and from collaborating fluidly. It is, arguably, impeding scientific progress. \n \nThis paper presents a roadmap for the development of Beatbox, a computer simulation environment for computational biology of the heart--an adaptable and extensible framework with which High Performance Computing may be harnessed by researchers.","PeriodicalId":247606,"journal":{"name":"BCS International Academic Conference","volume":"594 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BCS International Academic Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14236/EWIC/VOCS2008.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

Despite over a century's study, the trigger mechanisms of cardiac arrhythmias are poorly understood. Even modern experimental methods do not provide sufficient temporal and spacial resolution to trace the development of fibrillation in samples of cardiac tissue, not to mention the heart in vivo. Advances in human genetics provide information on the impact of certain genes on cellular activity, but do not explain the resultant mechanisms by which fibrillation arises. Thus, for some genetic cardiac diseases, the first presenting symptom is death. Computer simulations of electrical activity in cardiac tissue offer increasingly detailed insight into these phenomena, providing a view of cellular-level activity on the scale of a whole tissue wall. Already, advances in this field have led to developments in our understanding of heart fibrillation and sudden cardiac death and their impact is expected to increase significantly as we approach the ultimate goal of whole-heart modelling. Modelling the propagation of Action Potential through cardiac tissue is computationally expensive due to the huge number of equations per cell and the vast spacial and temporal scales required. The complexity of the problem encompasses the description of ionic currents underlying excitation of a single cell through the inhomogeneity of the tissue to the complex geometry of the whole heart. The timely running of computational models of cardiac tissue is increasingly dependant on the effective use of High Performance Computing (HPC), i.e. systems with parallel processors. Current state of the art cardiac simulation tools are limited either by the availability of modern, detailed models, or by their hardware portability or ease of use. The miscellany of current model implementations leads many researchers to develop their own ad-hoc software, preventing them from both utilising the power of HPC effectively, and from collaborating fluidly. It is, arguably, impeding scientific progress. This paper presents a roadmap for the development of Beatbox, a computer simulation environment for computational biology of the heart--an adaptable and extensible framework with which High Performance Computing may be harnessed by researchers.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Beatbox -心脏计算生物学的计算机模拟环境
尽管经过了一个多世纪的研究,但人们对心律失常的触发机制知之甚少。即使是现代实验方法也不能提供足够的时间和空间分辨率来追踪心脏组织样本中纤颤的发展,更不用说体内的心脏了。人类遗传学的进步提供了某些基因对细胞活动影响的信息,但不能解释纤维性颤动产生的最终机制。因此,对于一些遗传性心脏病,首先出现的症状是死亡。心脏组织电活动的计算机模拟为这些现象提供了越来越详细的见解,提供了整个组织壁尺度上细胞水平活动的视图。这一领域的进展已经使我们对心脏颤动和心源性猝死的理解有所发展,随着我们接近全心建模的最终目标,它们的影响预计会显著增加。模拟动作电位在心脏组织中的传播在计算上是昂贵的,因为每个细胞都需要大量的方程和巨大的空间和时间尺度。这个问题的复杂性包括描述单个细胞通过组织的不均匀性激发到整个心脏的复杂几何结构的离子电流。心脏组织计算模型的及时运行越来越依赖于高性能计算(HPC)的有效使用,即具有并行处理器的系统。目前最先进的心脏模拟工具受到现代,详细模型的可用性或其硬件可移植性或易用性的限制。当前模型实现的杂乱导致许多研究人员开发他们自己的ad-hoc软件,这既阻碍了他们有效地利用HPC的能力,也阻碍了他们流畅地协作。可以说,它阻碍了科学进步。本文提出了Beatbox的发展路线图,Beatbox是一个用于心脏计算生物学的计算机模拟环境——一个可适应和可扩展的框架,研究人员可以利用高性能计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Brain-Like Approximate Reasoning Incremental Connectivity-Based Outlier Factor Algorithm On the Complexity of Parity Games Spontaneous Pain Expression Recognition in Video Sequences A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1