@article{Raden-2018-teaching,
author = {Raden, Martin and Mohamed, Mostafa M and Ali, Syed M and Backofen, Rolf},
title = {Interactive implementations of thermodynamics-based {RNA}
structure and {RNA-RNA} interaction prediction approaches
for example-driven teaching},
journal = {PLOS Comput. Biol},
volume = {14},
number = {8},
pages = {e1006341},
year = {2018},
doi = {10.1371/journal.pcbi.1006341},
issn = {1553-734X},
issn = 	 {1553-7358},
user = {mmann},
abstract = {The investigation of RNA-based regulation of cellular processes is becoming an
increasingly important part of biological or medical research. For the analysis of this
type of data, RNA-related prediction tools integrated into of many pipelines and
workflows. In order to correctly apply and tune these programs, the user has to have a
precise understanding of their limitations and concepts. Within this manuscript, we
provide the mathematical foundations and extract the algorithmic ideas that are core to
state-of-the-art RNA structure and RNA-RNA interaction prediction algorithms. To
allow the reader to change and adapt the algorithms or to play with different inputs, we
provide an open-source web interface to JavaScript implementations and visualizations
of each algorithm.
The conceptual, teaching-focused presentation enables a high-level survey of the
approaches while providing sufficient details for understanding important concepts.
This is boosted by the simple generation and study of examples using the web interface
available under http://rna.informatik.uni-freiburg.de/Teaching/. In combination, we
provide a valuable resource for teaching, learning and understanding the discussed
prediction tools and thus enable a more informed analysis of RNA-related effects.}
}