Maureen R Smith1, Redmond P Smyth2, Roland Marquet2, Max von Kleist1. 1. Systems Pharmacology & Disease Control, Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany. 2. Architecture et Réactivité de l'ARN, Institut de Biologie Moléculaire et Cellulaire du Centre National de la Recherche Scientifique, Université de Strasbourg, Strasbourg, France.
Abstract
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 Analysis Tool). 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.deSupplementary information: Supplementary data are available at Bioinformatics online.
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 Analysis Tool). 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.deSupplementary information: Supplementary data are available at Bioinformatics online.
Authors: Redmond P Smyth; Maureen R Smith; Anne-Caroline Jousset; Laurence Despons; Géraldine Laumond; Thomas Decoville; Pierre Cattenoz; Christiane Moog; Fabrice Jossinet; Marylène Mougel; Jean-Christophe Paillart; Max von Kleist; Roland Marquet Journal: Nucleic Acids Res Date: 2018-05-18 Impact factor: 16.971
Authors: Winfried Goettsch; Niko Beerenwinkel; Li Deng; Lars Dölken; Bas E Dutilh; Florian Erhard; Lars Kaderali; Max von Kleist; Roland Marquet; Jelle Matthijnssens; Shawna McCallin; Dino McMahon; Thomas Rattei; Ronald P Van Rij; David L Robertson; Martin Schwemmle; Noam Stern-Ginossar; Manja Marz Journal: Viruses Date: 2021-04-27 Impact factor: 5.818