• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

意大利、欧洲和国际神经信息学研究进展概述。

Italian, European, and international neuroinformatics efforts: An overview.

机构信息

Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Scientific Directorate, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.

出版信息

Eur J Neurosci. 2023 Jun;57(12):2017-2039. doi: 10.1111/ejn.15854. Epub 2022 Dec 14.

DOI:10.1111/ejn.15854
PMID:36310103
Abstract

Neuroinformatics is a research field that focusses on software tools capable of identifying, analysing, modelling, organising and sharing multiscale neuroscience data. Neuroinformatics has exploded in the last two decades with the emergence of the Big Data phenomenon, characterised by the so-called 3Vs (volume, velocity and variety), which provided neuroscientists with an improved ability to acquire and process data faster and more cheaply thanks to technical improvements in clinical, genomic and radiological technologies. This situation has led to a 'data deluge', as neuroscientists can routinely collect more study data in a few days than they could in a year just a decade ago. To address this phenomenon, several neuroimaging-focussed neuroinformatics platforms have emerged, funded by national or transnational agencies, with the following goals: (i) development of tools for archiving and organising analytical data (XNAT, REDCap and LabKey); (ii) development of data-driven models evolving from reductionist approaches to multidimensional models (RIN, IVN, HBD, EuroPOND, E-DADS and GAAIN BRAIN); and (iii) development of e-infrastructures to provide sufficient computational power and storage resources (neuGRID, HBP-EBRAINS, LONI and CONP). Although the scenario is still fragmented, there are technological and economical attempts at both national and international levels to introduce high standards for open and Findable, Accessible, Interoperable and Reusable (FAIR) neuroscience worldwide.

摘要

神经信息学是一个专注于软件开发的研究领域,这些软件工具能够识别、分析、建模、组织和共享多尺度神经科学数据。随着大数据现象的出现,神经信息学在过去二十年中得到了迅猛发展,其特点是所谓的“3V”(即体量、速度和种类繁多),这使得神经科学家能够通过临床、基因组和放射技术的技术改进,更快、更廉价地获取和处理数据。这种情况导致了“数据泛滥”,因为神经科学家现在可以在几天内收集到比十年前一年还要多的研究数据。为了解决这一现象,一些专注于神经影像学的神经信息学平台已经出现,这些平台由国家或跨国机构资助,目标如下:(i)开发用于归档和组织分析数据的工具(XNAT、REDCap 和 LabKey);(ii)开发从还原方法演变为多维模型的数据驱动模型(RIN、IVN、HBD、EuroPOND、E-DADS 和 GAAIN BRAIN);(iii)开发电子基础设施,以提供足够的计算能力和存储资源(neuGRID、HBP-EBRAINS、LONI 和 CONP)。尽管目前情况仍然分散,但在国家和国际层面都在尝试引入高标准的开放、可查找、可访问、可互操作和可重复使用(FAIR)的神经科学技术。

相似文献

1
Italian, European, and international neuroinformatics efforts: An overview.意大利、欧洲和国际神经信息学研究进展概述。
Eur J Neurosci. 2023 Jun;57(12):2017-2039. doi: 10.1111/ejn.15854. Epub 2022 Dec 14.
2
Is Neuroscience FAIR? A Call for Collaborative Standardisation of Neuroscience Data.神经科学是否公平?呼吁合作标准化神经科学数据。
Neuroinformatics. 2022 Apr;20(2):507-512. doi: 10.1007/s12021-021-09557-0. Epub 2022 Jan 21.
3
Big data from small data: data-sharing in the 'long tail' of neuroscience.从小数据到大数据:神经科学“长尾”中的数据共享。
Nat Neurosci. 2014 Nov;17(11):1442-7. doi: 10.1038/nn.3838.
4
The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.神经科学数据共享的过去、现在与未来:关于促进可获取、可互操作、可重用和可理解(FAIR)实践与基础设施状况的观点
Front Neuroinform. 2024 Jan 5;17:1276407. doi: 10.3389/fninf.2023.1276407. eCollection 2023.
5
Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience.神经信息学:共享数据库与工具的整合助力整合神经科学发展。
J Integr Neurosci. 2002 Dec;1(2):117-28. doi: 10.1142/s0219635202000128.
6
Neuroinformatics and Computational Modelling as Complementary Tools for Neurotoxicology Studies.神经信息学和计算建模作为神经毒理学研究的补充工具。
Basic Clin Pharmacol Toxicol. 2018 Sep;123 Suppl 5:56-61. doi: 10.1111/bcpt.13075. Epub 2018 Sep 7.
7
Computational neuroscience and neuroinformatics: Recent progress and resources.计算神经科学与神经信息学:近期进展与资源
J Biosci. 2018 Dec;43(5):1037-1054.
8
A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility.开放与公平神经科学的标准组织:国际神经信息协调设施。
Neuroinformatics. 2022 Jan;20(1):25-36. doi: 10.1007/s12021-020-09509-0. Epub 2021 Jan 27.
9
Discovery and integrative neuroscience.发现与整合神经科学
Clin EEG Neurosci. 2005 Apr;36(2):55-63. doi: 10.1177/155005940503600204.
10
Global neuroinformatics: the International Neuroinformatics Coordinating Facility.全球神经信息学:国际神经信息学协调设施
J Neurosci. 2007 Apr 4;27(14):3613-5. doi: 10.1523/JNEUROSCI.0558-07.2007.

引用本文的文献

1
International Collaborations at the Intersection of Brain Sciences and Artificial Intelligence.脑科学与人工智能交叉领域的国际合作。
Neuroinformatics. 2025 Jun 21;23(3):36. doi: 10.1007/s12021-025-09736-3.
2
Harmonizing AI governance regulations and neuroinformatics: perspectives on privacy and data sharing.协调人工智能治理法规与神经信息学:关于隐私和数据共享的观点
Front Neuroinform. 2024 Dec 17;18:1472653. doi: 10.3389/fninf.2024.1472653. eCollection 2024.
3
A modular framework for multi-scale tissue imaging and neuronal segmentation.
用于多尺度组织成像和神经元分割的模块化框架。
Nat Commun. 2024 May 22;15(1):4102. doi: 10.1038/s41467-024-48146-y.
4
Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA.基于可解释 MRI 的机器学习算法 MUQUBIA 对神经退行性痴呆的鉴别诊断。
Sci Rep. 2023 Oct 13;13(1):17355. doi: 10.1038/s41598-023-43706-6.