The RNAwolf package

[Tags: gpl, library, program]

The algorithm implemented here-in provides extended RNA secondary structure prediction. Each predicted nucleotide pairing is extended with an annotation describing which of three nucleotide edges is engaged in the pairing. In addition, each nucleotide may be engaged in more than one pairing.

The algorithm is described in

Hoener zu Siederdissen C, Bernhart SH, Stadler PF, Hofacker IL,

A Folding Algorithm for Extended RNA Secondary Structures,

Bioinformatics (2011) 27 (13), i129-136

http://www.tbi.univie.ac.at/software/rnawolf/

Please note that experimental does mean experimental. We are mostly concerned with determining a good set of (heuristic) rules for run-time reduction currently. This version does include stacking and is able to fold sequences of a few hundred nucleotides in seconds.

Triplet calculations will come back with the next version (in a few days). The recursions require a number of changes to keep the runtimes down (as has been done for the extended loops without triplets).

We have recently split the Biohaskell libraries into smaller individual libraries. In addition, stacking, intermediate arrays, fusion and newtype-wrapping did require a number of changes. Please send a mail, if you encounter strange behaviour or bugs.

Changes in 0.3.2.0

Changes in 0.3.1.0


Properties

Versions0.3.0.0, 0.3.0.1, 0.3.0.2, 0.3.1.0, 0.3.2.0, 0.4.0.0
Dependenciesbase (==4.*), BiobaseTrainingData (>=0.1.2.2), BiobaseXNA, bytestring, cmdargs (==0.7.*), containers, deepseq, directory, parallel, PrimitiveArray, random, split, StatisticalMethods, vector
LicenseGPL-3
CopyrightChristian Hoener zu Siederdissen, 2010-2011
AuthorChristian Hoener zu Siederdissen, Stephan H Bernhart, Peter F Stadler, Ivo L Hofacker
Maintainerchoener@tbi.univie.ac.at
Stabilityexperimental
CategoryBioinformatics
Home pagehttp://www.tbi.univie.ac.at/software/rnawolf/
ExecutablesRNAwolf, RNAwolfTrain
Upload dateMon Sep 5 17:12:30 UTC 2011
Uploaded byChristianHoener
Downloads514 total (46 in last 30 days)

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