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Oxford University Press (OUP), Bioinformatics, 21(32), p. 3369-3370

DOI: 10.1093/bioinformatics/btw479

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MIMEAnTo: profiling functional RNA in mutational interference mapping experiments

Journal article published in 2016 by Maureen R. Smith, Redmond P. Smyth, Roland Marquet, Max von Kleist ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Summary: The mutational interference mapping experiment (MIME) is a powerful method that, coupled to a bioinformatics analysis pipeline, allows the identification of domains and structures in RNA that are important for its function. In MIME, target RNAs are randomly mutated, selected by function, physically separated and sequenced using next-generation sequencing (NGS). Quantitative effects of each mutation at each position in the RNA can be recovered with statistical certainty using the herein developed user-friendly, cross-platform software MIMEAnTo ( MIME An alysis To ol). Availability and implementation: MIMEAnTo is implemented in C ++ using the boost library as well as Qt for the graphical user interface and is distributed under GPL ( http://www.gnu.org/licences/gpl ). The libraries are statically linked in a stand alone executable and are not required on the system. The plots are generated with gnuplot. Gnuplot-iostream ( https://github.com/dstahlke/gnuplot-iostream ) serves as gnuplot interface. Standalone executables including examples and source code can be downloaded from https://github.com/maureensmith/MIMEAnTo . Contacts: msmith@zedat.fu-berlin.de or vkleist@zedat.fu-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online.