CARMEN e-Science Portal

CARMEN 电子科学门户

基本信息

  • 批准号:
    BB/I000984/1
  • 负责人:
  • 金额:
    $ 89.66万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2010
  • 资助国家:
    英国
  • 起止时间:
    2010 至 无数据
  • 项目状态:
    已结题

项目摘要

The study of the brain and of nervous systems is one of the priority areas for biological research in the UK and internationally. Neuroscience research commonly employs techniques that generate large data files (called time-series data) that record the activity of one or many nerve cells as well as other accompanying data, such as physiological measures, behaviour, or a stimulus that is used to activate the system. This mass of data requires detailed analysis in order to extract the important information and to look for patterns which can provide insight into the way the brain functions. CARMEN (an acronym for Code Analysis, Repository and Modelling for e-Neuroscience) harnesses the power of the web in order to enable researchers to accomplish this analysis and at the same time provide a way to share data, either within private user groups or openly within the science community. Starting in October 2006 a collaborative effort between computer scientists and neuroscientists at 11 UK universities has developed the first version of this resource. Using remote access through a web portal users can upload their data files to the CARMEN platform. At the same time the system allows information about the experiment and the data files (metadata) to be gathered so that others can understand the experiment. Users can also upload software tools that can be used to analyse the data or use tools provided by others in the community. We are also developing ways that the upload can happen whilst the experiment is being performed in order that collaborators can perform recording and analysis at the same time (real time distributed collaboration). Importantly, CARMEN has been developed so that this sharing of the resource is not restricted by the format of the files used to capture the data or the way in which the analysis methods have been written (interoperability). There is also a security structure that allows users to initially work on the files privately but, once the data have been published the data files can be made public so that others can use them. In this way CARMEN can both curate experimental data and provide a resource for secondary analysis or combination of data from different laboratories. This ability to reuse data adds significantly to their value, particularly for experiments that are complex to perform or which employ rare tissue. The current project will maintain and develop the CARMEN portal for a further four years. Importantly the project will support the transition from the initial development stage to a wider community engagement. This will involve Help Desk support for new users, troubleshooting of system problems, and further development of the web portal in response to user feedback. In addition, we will undertake development of new functions to allow specific data types to be uploaded, shared and analysed. In this respect we will focus effort on two main areas: (i) electroencephalogram (EEG) recordings and the brain responses to stimuli (event-related potentials), and (ii) neural activity data that can be extracted from video images. In the latter case this will enable CARMEN to be used for recordings that employ the latest generation of optical recording techniques. Finally, we will develop ways to link into other bioinformatics projects in order that details of brain structure, gene expresion, etc. might be stored and analysed at the same time. This last effort will be assisted by our involvement with the International Neuroinformatics Coordinating Facility (INCF) which was recently established to support links between databases and informatics resources in neuroscience. CARMEN is a unique facility that has addressed the specific issues of storing and analysing neurophysiological data on the web in order to facilitate collaboration and data sharing. With future development of the computing power of the web (cloud computing) it is likely that this will increasingly become the accepted method of research.
大脑和神经系统的研究是英国和国际生物学研究的优先领域之一。神经科学研究通常采用生成大型数据文件(称为时间序列数据)的技术,这些数据文件记录了一个或多个神经细胞的活动以及其他伴随数据,例如生理测量,行为或用于激活系统的刺激。这些大量的数据需要详细的分析,以提取重要的信息,并寻找可以深入了解大脑功能的模式。CARMEN(Code Analysis,Repository and Modelling for e-Neuroscience的缩写)利用网络的力量,使研究人员能够完成这种分析,同时提供一种在私人用户组或科学界公开共享数据的方法。从2006年10月开始,英国11所大学的计算机科学家和神经科学家合作开发了该资源的第一版。通过门户网站进行远程访问,用户可以将其数据文件上传到CARMEN平台。同时,该系统允许收集有关实验和数据文件(元数据)的信息,以便其他人可以理解实验。用户还可以上传可用于分析数据的软件工具或使用社区中其他人提供的工具。我们还在开发在实验进行的同时进行上传的方法,以便协作者可以同时进行记录和分析(真实的时间分布式协作)。重要的是,CARMEN的开发使得资源共享不受用于捕获数据的文件格式或分析方法编写方式的限制(互操作性)。还有一个安全结构,允许用户最初私下处理文件,但一旦数据发布,数据文件就可以公开,以便其他人可以使用它们。通过这种方式,CARMEN既可以管理实验数据,又可以为来自不同实验室的数据的二次分析或组合提供资源。这种重复使用数据的能力大大增加了它们的价值,特别是对于执行复杂或使用稀有组织的实验。目前的项目将在今后四年内维持和发展CARMEN门户网站。重要的是,该项目将支持从最初的开发阶段过渡到更广泛的社区参与。这将涉及服务台为新用户提供支助,解决系统问题,并根据用户反馈意见进一步开发门户网站。此外,我们将开发新功能,以便上传、共享和分析特定数据类型。在这方面,我们将集中精力在两个主要领域:(i)脑电图(EEG)记录和大脑对刺激的反应(事件相关电位),以及(ii)可以从视频图像中提取的神经活动数据。在后一种情况下,这将使CARMEN能够用于采用最新一代光学记录技术的记录。最后,我们将开发连接到其他生物信息学项目的方法,以便同时存储和分析大脑结构,基因表达等的细节。这最后的努力将有助于我们参与国际神经信息学协调机构(INCF),这是最近成立的,以支持神经科学数据库和信息资源之间的联系。CARMEN是一个独特的设施,它解决了在网络上存储和分析神经生理数据的具体问题,以促进合作和数据共享。随着网络计算能力(云计算)的未来发展,这可能会越来越多地成为公认的研究方法。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A data repository and analysis framework for spontaneous neural activity recordings in developing retina.
  • DOI:
    10.1186/2047-217x-3-3
  • 发表时间:
    2014-03-26
  • 期刊:
  • 影响因子:
    9.2
  • 作者:
    Eglen SJ;Weeks M;Jessop M;Simonotto J;Jackson T;Sernagor E
  • 通讯作者:
    Sernagor E
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James Austin其他文献

Alternatives to the Secure Detention and Confinement of Juvenile Offenders
安全拘留和监禁少年犯的替代办法
  • DOI:
  • 发表时间:
    2005
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Austin;Kelly Johnson;Ronald Weitzer
  • 通讯作者:
    Ronald Weitzer
Initial Development of Scales to Assess Self-Efficacy for Disclosing HIV Status and Negotiating Safer Sex in HIV-Positive Persons
  • DOI:
    10.1023/a:1011300912395
  • 发表时间:
    2001-09-01
  • 期刊:
  • 影响因子:
    2.400
  • 作者:
    Seth C. Kalichman;David Rompa;Kari DiFonzo;Dolores Simpson;Florence Kyomugisha;James Austin;Webster Luke
  • 通讯作者:
    Webster Luke
ENAMeL: A Language for Binary Correlation Matrix Memories
  • DOI:
    10.1007/s11063-013-9307-8
  • 发表时间:
    2013-06-13
  • 期刊:
  • 影响因子:
    2.800
  • 作者:
    Nathan Burles;Simon O’Keefe;James Austin;Stephen Hobson
  • 通讯作者:
    Stephen Hobson
The Empirical Case for Pretrial Risk Assessment Instruments
审前风险评估工具的实证案例
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    2.1
  • 作者:
    Sarah L. Desmarais;J. Monahan;James Austin
  • 通讯作者:
    James Austin
Evaluating How Well Your Classification System is Operating: A Practical Approach
评估分类系统的运行情况:实用方法
  • DOI:
  • 发表时间:
    1986
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Austin
  • 通讯作者:
    James Austin

James Austin的其他文献

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{{ truncateString('James Austin', 18)}}的其他基金

DISSERTATION RESEARCH: Integrating Ecology and Evolution to Infer Hierarchical Processes Structuring Slender-snouted Crocodile Populations in Central Africa
论文研究:整合生态学和进化论来推断中部非洲细吻鳄鱼种群的分层过程
  • 批准号:
    1010574
  • 财政年份:
    2010
  • 资助金额:
    $ 89.66万
  • 项目类别:
    Standard Grant

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