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

Weihang Zhang, Jinli Suo*, Yan Yan, Runzhao Yang, Yiming Lu, Yiqi Jin, Shuochen Gao, Shao Li, Juntao Gao*, Michael Zhang*, Qionghai Dai*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)8348-8366
页数19
期刊Nucleic Acids Research
51
16
DOI
出版状态已出版 - 8 9月 2023
已对外发布

指纹

探究 'iSMOD: an integrative browser for image-based single-cell multi-omics data' 的科研主题。它们共同构成独一无二的指纹。

引用此