首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   5篇
  免费   0篇
  2016年   1篇
  2014年   2篇
  2013年   2篇
排序方式: 共有5条查询结果,搜索用时 15 毫秒
1
1.
2.
3.
4.
5.
We developed multiple gene expression pipelines and assembled them into a web-based tool called Pop’s Pipes to facilitate preprocessing and analysis of substantial poplar gene expression data. The input data can be spatiotemporal microarray and RNA-seq data from comparable tissues, time points, or treatment-vs-control conditions. Pop’s Pipes can be used to identify differentially expressed genes between one or multiple paired tissues, time points, or treatment-vs-control conditions in a single in silico analysis. The differentially expressed genes (DEGs) obtained for each comparison will be automatically analyzed by Pop’s Pipes for identifying significantly enriched gene ontologies and interpro protein domains. Also, significantly changed metabolic pathways across all input data sets will be identified. We also integrated a pipeline into Pop's Pipes for constructing any of three type gene ontology trees when a short list of gene ontologies from biological processes, molecular functions, or cellular components is used as an input. The resulting information from Pop’s Pipes enables scrutiny to create spatiotemporal models and hypotheses to understand how poplar develops and functions. Pop’s Pipes can analyze a microarray or RNA-seq data set with 10 time points in 4–10 h, with each time point containing three replicates of treatments and three controls. Such a data set usually takes a bioinformatician a few months to a year to analyze. Pop’s Pipes can thus save users tremendous amounts of research time when large numbers of comparative data need to be analyzed.  相似文献   
1
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号