一个基于云的学习模块,用于生物标志物发现
Christopher L Hemme1,2, Laura Beaudry3, Zelaikha Yosufzai4
1Department of Biomedical and Pharmaceutical Sciences, College of Pharmacy, University of Rhode Island, Kingston RI, USA.
Briefings in bioinformatics
|July 23, 2024
概括
本研究介绍了一种基于云的学习模块,用于生物标志物发现,利用 Jupyter Notebooks 与 R 和 Bioconductor 进行交互式数据分析. 该模块提供了omics数据分析和机器学习的实践培训,用于识别生物标志物.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 生物标志物的发现对于疾病的诊断和治疗至关重要.
- 访问交互式,基于云的学习资源来进行复杂的数据分析是有限的.
- 基于云的学习的NIGMS沙盒旨在弥合这一差距.
研究的目的:
- 开发和描述一个基于云的培训模块,用于生物标志物发现.
- 提供使用R和生物导体分析omics数据的交互式学习材料.
- 将这些资源通过NIGMS沙盒平台公开提供.
主要方法:
- 使用 Jupyter Notebooks 开发一个由九个子模块组成的训练模块.
- 利用R和生物导体用于生物标志物和omics数据分析.
- 在谷歌云平台上部署以进行交互式基于云的数据访问和分析.
主要成果:
- 该模块涵盖了重要的生物标志物发现主题,包括数据分析和机器学习.
- 互动元素,如在线测验和概述视频,可以增强自我评估和学习.
- 该模块可以通过NIGMS沙盒公开访问.
结论:
- 开发的模块为生物标志物发现提供了一个有价值的,互动的,基于云的教育资源.
- 这个倡议提高了高级生物信息学培训的可访问性.
- 该平台支持omics数据分析中的自主学习.
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