Kumar Sudhir, Konikoff Charlotte, Sanderford Maxwell, Liu Li, Newfeld Stuart, Ye Jieping, Kulathinal Rob J
Institute for Genomic and Evolutionary Medicine and.
Department of Biomedical Informatics and.
G3 (Bethesda). 2017 Aug 7;7(8):2791-2797. doi: 10.1534/g3.117.040345.
Gene expression patterns assayed across development can offer key clues about a gene's function and regulatory role. is ideal for such investigations as multiple individual and high-throughput efforts have captured the spatiotemporal patterns of thousands of embryonic expressed genes in the form of images. FlyExpress (www.flyexpress.net), a knowledgebase based on a massive and unique digital library of standardized images and a simple search engine to find coexpressed genes, was created to facilitate the analytical and visual mining of these patterns. Here, we introduce the next generation of FlyExpress resources to facilitate the integrative analysis of sequence data and spatiotemporal patterns of expression from images. FlyExpress 7 now includes over 100,000 standardized images and implements a more efficient, user-defined search algorithm to identify coexpressed genes via Genomewide Expression Maps (GEMs). Shared motifs found in the upstream 5' regions of any pair of coexpressed genes can be visualized in an interactive dotplot. Additional webtools and link-outs to assist in the downstream validation of candidate motifs are also provided. Together, FlyExpress 7 represents our largest effort yet to accelerate discovery via the development and dispersal of new webtools that allow researchers to perform data-driven analyses of coexpression (image) and genomic (sequence) data.
在整个发育过程中检测到的基因表达模式可以为基因的功能和调控作用提供关键线索。由于多项个体研究和高通量研究已经以图像的形式捕捉到了数千个胚胎表达基因的时空模式,因此这对于此类研究来说是理想的。FlyExpress(www.flyexpress.net)是一个知识库,它基于一个庞大且独特的标准化图像数字库以及一个用于查找共表达基因的简单搜索引擎而创建,旨在促进对这些模式的分析和可视化挖掘。在这里,我们介绍下一代FlyExpress资源,以促进对序列数据和图像表达时空模式的综合分析。FlyExpress 7现在包含超过100,000张标准化图像,并实现了一种更高效的、用户定义的搜索算法,通过全基因组表达图谱(GEMs)来识别共表达基因。在任何一对共表达基因的上游5'区域中发现的共享基序可以在交互式点图中可视化。还提供了其他网络工具和链接,以协助对候选基序进行下游验证。总之,FlyExpress 7代表了我们迄今为止最大的努力,即通过开发和推广新的网络工具来加速发现,这些工具使研究人员能够对共表达(图像)和基因组(序列)数据进行数据驱动的分析。