A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry

Samuel Wein; Byron Andrews; Timo Sachsenberg; Helena Santos-Rosa; Oliver Kohlbacher; Tony Kouzarides; Benjamin A. Garcia; Hendrik Weisser

doi:10.1038/s41467-020-14665-7

Nature Communications (Feb 2020)

A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry

Samuel Wein,
Byron Andrews,
Timo Sachsenberg,
Helena Santos-Rosa,
Oliver Kohlbacher,
Tony Kouzarides,
Benjamin A. Garcia,
Hendrik Weisser

Affiliations

Samuel Wein: Epigenetics Program, Perelman School of Medicine, University of Pennsylvania
Byron Andrews: STORM Therapeutics Limited, Moneta Building, Babraham Research Campus
Timo Sachsenberg: Applied Bioinformatics, Department for Computer Science, University of Tübingen
Helena Santos-Rosa: Gurdon Institute, University of Cambridge
Oliver Kohlbacher: Center for Bioinformatics Tübingen, University of Tübingen
Tony Kouzarides: Gurdon Institute, University of Cambridge
Benjamin A. Garcia: Epigenetics Program, Perelman School of Medicine, University of Pennsylvania
Hendrik Weisser: STORM Therapeutics Limited, Moneta Building, Babraham Research Campus

DOI: https://doi.org/10.1038/s41467-020-14665-7
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 12

Abstract

Read online

Mass spectrometry (MS) enables identification of modified RNA residues, but high-throughput processing is currently a bottleneck. Here, the authors present a free and open-source database search engine for RNA MS data to facilitate reliable identification of modified RNA sequences.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal