BrainDead
BrainDead - RNA classification via accessible k-mers
BrainDead learns and predicts a two-class model for short RNA
sequences based on accessibility-enhanced k-mer features.
That is, the model considers
whether or not k-mers are covered by intra-molecular or homo-dimer
base pairs of stable structures or RNA-RNA interactions.
For articles describing the tool and webserver refer to the reference section below. Please
cite us when using our tools.
For more information check the help page.
Try BrainDead with this
example: miRNAs as ligands for microglia activation (
input|
result)
When using BrainDead please cite :
- Martin Raden, Thomas Wallach, Milad Miladi, Yuanyuan Zhai, Christina Krueger, Zoe J. Mossmann, Paul Dembny, Rolf Backofen, Seija Lehnardt
Structure-aware machine learning classification of oligonucleotide-induced immune response identifies microRNAs operating as Toll-like receptor 7/8 ligands
RNA Biology, 18:sup1, 268-277,2021.
- Martin Raden, Syed M Ali, Omer S Alkhnbashi, Anke Busch, Fabrizio Costa, Jason A Davis, Florian Eggenhofer, Rick Gelhausen, Jens Georg, Steffen Heyne, Michael Hiller, Kousik Kundu, Robert Kleinkauf, Steffen C Lott, Mostafa M Mohamed, Alexander Mattheis, Milad Miladi, Andreas S Richter, Sebastian Will, Joachim Wolff, Patrick R Wright, and Rolf Backofen
Freiburg RNA tools: a central online resource for RNA-focused research and teaching
Nucleic Acids Research, 46(W1), W25-W29, 2018.
Results are computed with BrainDead version 1.0.1 using IntaRNA 3.1.5 and Vienna RNA package 2.4.14