Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

RNALocate

General information

URL: http://www.rnalocate.org/
Full name: database for RNA subcellular localization
Description: RNALocate is a web-accessible database that aims to provide a high-quality RNA subcellular localization resource and facilitate future researches on RNA function or structure. RNALocate v3.0 is a comprehensive, upgraded repository cataloging the dynamic subcellular localization of diverse RNA types across numerous species and cellular conditions, integrating over 850 sequencing datasets and covering 1.8 million entries. It uniquely provides a machine learning-based prediction tool (using CNNs and Transformers) for localizing seven RNA types across eleven cellular compartments.
Year founded: 2017
Last update: 2024-10-15
Version: v3.0
Accessibility:
Accessible
Country/Region: China

Classification & Tag

Data type:
RNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Southern Medical University
Address: Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
City: Guangzhou
Province/State: Guangdong
Country/Region: China
Contact name (PI/Team): Wang Dong
Contact email (PI/Helpdesk): wangdong79@smu.edu.cn

Publications

39404071
RNALocate v3.0: Advancing the Repository of RNA Subcellular Localization with Dynamic Analysis and Prediction. [PMID: 39404071]
Wu L, Wang L, Hu S, Tang G, Chen J, Yi Y, Xie H, Lin J, Wang M, Wang D, Yang B, Huang Y.

Subcellular localization of RNA is a crucial mechanism for regulating diverse biological processes within cells. Dynamic RNA subcellular localizations are essential for maintaining cellular homeostasis; however, their distribution and changes during development and differentiation remain largely unexplored. To elucidate the dynamic patterns of RNA distribution within cells, we have upgraded RNALocate to version 3.0, a repository for RNA-subcellular localization (http://www.rnalocate.org/ or http://www.rna-society.org/rnalocate/). RNALocate v3.0 incorporates and analyzes RNA subcellular localization sequencing data from over 850 samples, with a specific focus on the dynamic changes in subcellular localizations under various conditions. The species coverage has also been expanded to encompass mammals, non-mammals, plants and microbes. Additionally, we provide an integrated prediction algorithm for the subcellular localization of seven RNA types across eleven subcellular compartments, utilizing convolutional neural networks (CNNs) and transformer models. Overall, RNALocate v3.0 contains a total of 1 844 013 RNA-localization entries covering 26 RNA types, 242 species and 177 subcellular localizations. It serves as a comprehensive and readily accessible data resource for RNA-subcellular localization, facilitating the elucidation of cellular function and disease pathogenesis.

Nucleic Acids Res. 2025:53(D1) | 7 Citations (from Europe PMC, 2025-12-13)
34551440
RNALocate v2.0: an updated resource for RNA subcellular localization with increased coverage and annotation. [PMID: 34551440]
Cui T, Dou Y, Tan P, Ni Z, Liu T, Wang D, Huang Y, Cai K, Zhao X, Xu D, Lin H, Wang D.

Resolving the spatial distribution of the transcriptome at a subcellular level can increase our understanding of biology and diseases. To facilitate studies of biological functions and molecular mechanisms in the transcriptome, we updated RNALocate, a resource for RNA subcellular localization analysis that is freely accessible at http://www.rnalocate.org/ or http://www.rna-society.org/rnalocate/. Compared to RNALocate v1.0, the new features in version 2.0 include (i) expansion of the data sources and the coverage of species; (ii) incorporation and integration of RNA-seq datasets containing information about subcellular localization; (iii) addition and reorganization of RNA information (RNA subcellular localization conditions and descriptive figures for method, RNA homology information, RNA interaction and ncRNA disease information) and (iv) three additional prediction tools: DM3Loc, iLoc-lncRNA and iLoc-mRNA. Overall, RNALocate v2.0 provides a comprehensive RNA subcellular localization resource for researchers to deconvolute the highly complex architecture of the cell.

Nucleic Acids Res. 2022:50(D1) | 87 Citations (from Europe PMC, 2025-12-13)
27543076
RNALocate: a resource for RNA subcellular localizations. [PMID: 27543076]
Zhang T, Tan P, Wang L, Jin N, Li Y, Zhang L, Yang H, Hu Z, Zhang L, Hu C, Li C, Qian K, Zhang C, Huang Y, Li K, Lin H, Wang D.

Increasing evidence has revealed that RNA subcellular localization is a very important feature for deeply understanding RNA's biological functions after being transported into intra- or extra-cellular regions. RNALocate is a web-accessible database that aims to provide a high-quality RNA subcellular localization resource and facilitate future researches on RNA function or structure. The current version of RNALocate documents more than 37 700 manually curated RNA subcellular localization entries with experimental evidence, involving more than 21 800 RNAs with 42 subcellular localizations in 65 species, mainly including Homo sapiens, Mus musculus and Saccharomyces cerevisiae etc. Besides, RNA homology, sequence and interaction data have also been integrated into RNALocate. Users can access these data through online search, browse, blast and visualization tools. In conclusion, RNALocate will be of help in elucidating the entirety of RNA subcellular localization, and developing new prediction methods. The database is available at http://www.rna-society.org/rnalocate/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2017:45(D1) | 151 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
553/6895 (91.994%)
Expression:
91/1347 (93.318%)
553
Total Rank
231
Citations
28.875
z-index

Community reviews

Not Rated
Data quality & quantity:
Content organization & presentation
System accessibility & reliability:

Word cloud

Related Databases

Citing
Cited by

Record metadata

Created on: 2017-02-13
Curated by:
Yuhao Zeng [2025-08-05]
Xinyu Zhou [2023-09-19]
Xinyu Zhou [2023-09-14]
Lina Ma [2023-02-17]
Lina Ma [2023-02-11]
Pei Liu [2022-08-31]
Pei Liu [2022-05-15]
Lina Ma [2018-07-04]
Shixiang Sun [2017-02-13]