| Literature DB >> 31073612 |
Jörg Fallmann1, Pavankumar Videm2, Andrea Bagnacani3, Bérénice Batut2, Maria A Doyle4,5, Tomas Klingstrom6, Florian Eggenhofer2, Peter F Stadler1,7,8, Rolf Backofen2,9, Björn Grüning2,10.
Abstract
RNA has become one of the major research topics in molecular biology. As a central player in key processes regulating gene expression, RNA is in the focus of many efforts to decipher the pathways that govern the transition of genetic information to a fully functional cell. As more and more researchers join this endeavour, there is a rapidly growing demand for comprehensive collections of tools that cover the diverse layers of RNA-related research. However, increasing amounts of data, from diverse types of experiments, addressing different aspects of biological questions need to be consolidated and integrated into a single framework. Only then is it possible to connect findings from e.g. RNA-Seq experiments and methods for e.g. target predictions. To address these needs, we present the RNA Workbench 2.0 , an updated online resource for RNA related analysis. With the RNA Workbench we created a comprehensive set of analysis tools and workflows that enables researchers to analyze their data without the need for sophisticated command-line skills. This update takes the established framework to the next level, providing not only a containerized infrastructure for analysis, but also a ready-to-use platform for hands-on training, analysis, data exploration, and visualization. The new framework is available at https://rna.usegalaxy.eu , and login is free and open to all users. The containerized version can be found at https://github.com/bgruening/galaxy-rna-workbench.Entities:
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Year: 2019 PMID: 31073612 PMCID: PMC6602469 DOI: 10.1093/nar/gkz353
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971
Figure 1.Overview of RNA research topics, dedicated tools and example workflows in RNA target prediction enables to analyze potential interaction partners of RNA molecules. Included annotation tools allow the discovery of homologous sequences in genomes. The secondary structure of input RNA sequences can be predicted and visualized or for example used to create sequence-structure alignments. High-throughput and RNA sequencing data analysis can be performed with available tools and results directly intersected with e.g. databases for RNA-protein interactions.