iSMOD: an integrative browser for image-based single-cell multi-omics data

生物 组学 蛋白质组学 计算生物学 数据集成 生物信息学 数据科学 计算机科学 基因 遗传学 数据挖掘
作者
Weihang Zhang,Jinli Suo,Yan Yan,Runzhao Yang,Yongju Lu,Yiqi Jin,Shuo Gao,Shao Li,Juntao Gao,Michael Q. Zhang,Qionghai Dai
出处
期刊:Nucleic Acids Research [Oxford University Press]
卷期号:51 (16): 8348-8366
标识
DOI:10.1093/nar/gkad580
摘要

Abstract Genomic and transcriptomic image data, represented by DNA and RNA fluorescence in situ hybridization (FISH), respectively, together with proteomic data, particularly that related to nuclear proteins, can help elucidate gene regulation in relation to the spatial positions of chromatins, messenger RNAs, and key proteins. However, methods for image-based multi-omics data collection and analysis are lacking. To this end, we aimed to develop the first integrative browser called iSMOD (image-based Single-cell Multi-omics Database) to collect and browse comprehensive FISH and nucleus proteomics data based on the title, abstract, and related experimental figures, which integrates multi-omics studies focusing on the key players in the cell nucleus from 20 000+ (still growing) published papers. We have also provided several exemplar demonstrations to show iSMOD’s wide applications—profiling multi-omics research to reveal the molecular target for diseases; exploring the working mechanism behind biological phenomena using multi-omics interactions, and integrating the 3D multi-omics data in a virtual cell nucleus. iSMOD is a cornerstone for delineating a global view of relevant research to enable the integration of scattered data and thus provides new insights regarding the missing components of molecular pathway mechanisms and facilitates improved and efficient scientific research.
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