4.8 Article

RNALocate v2.0: an updated resource for RNA subcellular localization with increased coverage and annotation

Journal

NUCLEIC ACIDS RESEARCH
Volume 50, Issue D1, Pages D333-D339

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab825

Keywords

-

Funding

  1. National Key Research and Development Project of China [2017YFA0105001, 2019YFA0801800]
  2. National Natural Science Foundation of China [82070109, 81770104, 62002153]
  3. Guangdong Basic and Applied Basic Research Foundation [2019A1515010784, 2019A1515110701]
  4. China Postdoctoral Science Foundation [2020M682623, 2020M682785]
  5. Paul K. and Diane Shumaker Endowment Fund at University of Missouri
  6. National Key Research and Development Project of China

Ask authors/readers for more resources

RNALocate v2.0 is a comprehensive RNA subcellular localization resource that includes expanded data sources and species coverage, integration of RNA-seq datasets, addition and reorganization of RNA information, and three new prediction tools, providing researchers with tools to understand the complex architecture of the cell.
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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available