• 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

从数据到发现:神经信息学助力理解阿尔茨海默病

From data to discovery: Neuroinformatics in understanding Alzheimer's disease.

作者信息

Pahal Sonu, Pahal Vishvender, Chaudhary Amit

机构信息

Bioinformatics Program, University of Arkansas for Medical Sciences, University of Arkansas at Little Rock, Little Rock, AR, USA.

出版信息

J Biosci. 2025;50.

PMID:39703103
Abstract

Neuroinformatics, an interdisciplinary field integrating neuroscience and informatics, plays a crucial role in understanding the complexities of the brain and neurological diseases such as Alzheimer's disease (AD). This review explores the applications, databases, and tools used in neuroinformatics, focusing on their role in AD research. Neuroinformatics facilitates data integration, analysis, and modeling, enabling researchers to unravel the underlying mechanisms of AD pathology. Various databases and tools provide access to neuroimaging, and genetic and clinical data, facilitating collaborative research and the development of diagnostic and therapeutic strategies. Neuroinformatics holds promise in advancing our understanding and treatment of AD, offering insights into disease progression, biomarker identification, and personalized medicine approaches.

摘要

神经信息学是一个融合神经科学和信息学的跨学科领域,在理解大脑的复杂性以及诸如阿尔茨海默病(AD)等神经疾病方面发挥着关键作用。本综述探讨了神经信息学中使用的应用、数据库和工具,重点关注它们在AD研究中的作用。神经信息学促进数据整合、分析和建模,使研究人员能够揭示AD病理学的潜在机制。各种数据库和工具提供了获取神经影像学、基因和临床数据的途径,促进了合作研究以及诊断和治疗策略的开发。神经信息学在推进我们对AD的理解和治疗方面具有前景,为疾病进展、生物标志物识别和个性化医疗方法提供了见解。

相似文献

1
From data to discovery: Neuroinformatics in understanding Alzheimer's disease.从数据到发现:神经信息学助力理解阿尔茨海默病
J Biosci. 2025;50.
2
Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative.了解疾病进展和改善阿尔茨海默病临床试验:阿尔茨海默病神经影像学倡议的最新重点。
Alzheimers Dement. 2019 Jan;15(1):106-152. doi: 10.1016/j.jalz.2018.08.005. Epub 2018 Oct 13.
3
AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling.人工智能驱动的阿尔茨海默病创新:整合早期诊断、个性化治疗和预后建模。
Ageing Res Rev. 2024 Nov;101:102497. doi: 10.1016/j.arr.2024.102497. Epub 2024 Sep 16.
4
Revolution of Resting-State Functional Neuroimaging Genetics in Alzheimer's Disease.阿尔茨海默病静息态功能神经影像遗传学的变革
Trends Neurosci. 2017 Aug;40(8):469-480. doi: 10.1016/j.tins.2017.06.002. Epub 2017 Jul 3.
5
A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis.基于神经影像学的阿尔茨海默病异质性分析数据驱动方法综述。
Rev Neurosci. 2023 Jul 10;35(2):121-139. doi: 10.1515/revneuro-2023-0033. Print 2024 Feb 26.
6
Effect of HMGCR genetic variation on neuroimaging biomarkers in healthy, mild cognitive impairment and Alzheimer's disease cohorts.HMGCR基因变异对健康、轻度认知障碍和阿尔茨海默病队列中神经影像学生物标志物的影响。
Oncotarget. 2016 Mar 22;7(12):13319-27. doi: 10.18632/oncotarget.7797.
7
2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.阿尔茨海默病神经影像学计划2014年更新:自启动以来发表论文综述
Alzheimers Dement. 2015 Jun;11(6):e1-120. doi: 10.1016/j.jalz.2014.11.001.
8
Rare variants in the splicing regulatory elements of EXOC3L4 are associated with brain glucose metabolism in Alzheimer's disease.EXOC3L4 剪接调控元件中的罕见变异与阿尔茨海默病的大脑葡萄糖代谢有关。
BMC Med Genomics. 2018 Sep 14;11(Suppl 3):76. doi: 10.1186/s12920-018-0390-6.
9
AI for the prediction of early stages of Alzheimer's disease from neuroimaging biomarkers - A narrative review of a growing field.基于神经影像学生物标志物的阿尔茨海默病早期预测的人工智能——一个不断发展领域的综述。
Neurol Sci. 2024 Nov;45(11):5117-5127. doi: 10.1007/s10072-024-07649-8. Epub 2024 Jun 13.
10
Deciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.解析脂质代谢相关基因在阿尔茨海默病中的作用:一种整合中医的机器学习方法。
Front Endocrinol (Lausanne). 2024 Oct 23;15:1448119. doi: 10.3389/fendo.2024.1448119. eCollection 2024.