Fabian Kern1, Christina Backes1, Pascal Hirsch1, Tobias Fehlmann1, Martin Hart2, Eckart Meese2, Andreas Keller1,3,4,5. 1. Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, 66123, Germany and Department of Human Genetics, Saarland University, Homburg, 66424, Germany. 2. Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany and Department of Human Genetics, Saarland University Hospital, Homburg Germany. 3. Center for Bioinformatics, Saarland University, Saarbrücken, Germany. 4. School of Medicine Office, Stanford University, Stanford, CA, USA. 5. Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
Abstract
MOTIVATION: Since the initial discovery of microRNAs as post-transcriptional, regulatory key players in the 1990s, a total number of $2656$ mature microRNAs have been publicly described for Homo sapiens. As discovery of new miRNAs is still on-going, target identification remains to be an essential and challenging step preceding functional annotation analysis. One key challenge for researchers seems to be the selection of the most appropriate tool out of the larger multiverse of published solutions for a given research study set-up. RESULTS: In this review we collectively describe the field of in silico target prediction in the course of time and point out long withstanding principles as well as recent developments. By compiling a catalog of characteristics about the 98 prediction methods and identifying common and exclusive traits, we signpost a simplified mechanism to address the problem of application selection. Going further we devised interpretation strategies for common types of output as generated by frequently used computational methods. To this end, our work specifically aims to make prospective users aware of common mistakes and practical questions that arise during the application of target prediction tools. AVAILABILITY: An interactive implementation of our recommendations including materials shown in the manuscript is freely available at https://www.ccb.uni-saarland.de/mtguide.
MOTIVATION: Since the initial discovery of microRNAs as post-transcriptional, regulatory key players in the 1990s, a total number of $2656$ mature microRNAs have been publicly described for Homo sapiens. As discovery of new miRNAs is still on-going, target identification remains to be an essential and challenging step preceding functional annotation analysis. One key challenge for researchers seems to be the selection of the most appropriate tool out of the larger multiverse of published solutions for a given research study set-up. RESULTS: In this review we collectively describe the field of in silico target prediction in the course of time and point out long withstanding principles as well as recent developments. By compiling a catalog of characteristics about the 98 prediction methods and identifying common and exclusive traits, we signpost a simplified mechanism to address the problem of application selection. Going further we devised interpretation strategies for common types of output as generated by frequently used computational methods. To this end, our work specifically aims to make prospective users aware of common mistakes and practical questions that arise during the application of target prediction tools. AVAILABILITY: An interactive implementation of our recommendations including materials shown in the manuscript is freely available at https://www.ccb.uni-saarland.de/mtguide.
Authors: Fabian Kern; Lena Krammes; Karin Danz; Caroline Diener; Tim Kehl; Oliver Küchler; Tobias Fehlmann; Mustafa Kahraman; Stefanie Rheinheimer; Ernesto Aparicio-Puerta; Sylvia Wagner; Nicole Ludwig; Christina Backes; Hans-Peter Lenhof; Hagen von Briesen; Martin Hart; Andreas Keller; Eckart Meese Journal: Nucleic Acids Res Date: 2021-01-11 Impact factor: 16.971