Department of Biostatistics and Data Science, School of Public Health,The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX 77030, USA.
Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX 77030, USA.
Database (Oxford). 2020 Nov 28;2020. doi: 10.1093/database/baaa074.
The exponential growth of genomic/genetic data in the era of Big Data demands new solutions for making these data findable, accessible, interoperable and reusable. In this article, we present a web-based platform named Gene Expression Time-Course Research (GETc) Platform that enables the discovery and visualization of time-course gene expression data and analytical results from the NIH/NCBI-sponsored Gene Expression Omnibus (GEO). The analytical results are produced from an analytic pipeline based on the ordinary differential equation model. Furthermore, in order to extract scientific insights from these results and disseminate the scientific findings, close and efficient collaborations between domain-specific experts from biomedical and scientific fields and data scientists is required. Therefore, GETc provides several recommendation functions and tools to facilitate effective collaborations. GETc platform is a very useful tool for researchers from the biomedical genomics community to present and communicate large numbers of analysis results from GEO. It is generalizable and broadly applicable across different biomedical research areas. GETc is a user-friendly and efficient web-based platform freely accessible at http://genestudy.org/.
在大数据时代，基因组/遗传学数据呈指数级增长，这就需要新的解决方案来实现这些数据的可发现性、可访问性、互操作性和可重用性。在本文中，我们介绍了一个名为基因表达时间序列研究（GETc）平台的基于网络的平台，该平台能够发现和可视化来自美国国立卫生研究院/国家生物技术信息中心（NIH/NCBI）赞助的基因表达综合数据库（GEO）的时间序列基因表达数据和分析结果。分析结果是从基于常微分方程模型的分析管道中产生的。此外，为了从这些结果中提取科学见解并传播科学发现，需要生物医学和科学领域的特定领域专家与数据科学家之间进行紧密有效的合作。因此，GETc 提供了几个推荐功能和工具来促进有效的合作。GETc 平台是生物医学基因组学领域的研究人员展示和交流大量来自 GEO 的分析结果的非常有用的工具。它具有通用性，可以广泛应用于不同的生物医学研究领域。GETc 是一个用户友好且高效的基于网络的平台，可在 http://genestudy.org/ 上免费访问。
