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  • 标题:An informatics research platform to make public gene expression time-course datasets reusable for more scientific discoveries
  • 本地全文:下载
  • 作者:Patra, Braja Gopal ; Soltanalizadeh, Babak ; Deng, Nan
  • 期刊名称:Database
  • 印刷版ISSN:1758-0463
  • 电子版ISSN:1758-0463
  • 出版年度:2020
  • 卷号:2020
  • 页码:1-15
  • DOI:10.1093/database/baaa074
  • 出版社:Oxford University Press
  • 摘要: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.
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