Author: Elena Rivas
A software tool for prototyping single-sequence RNA secondary structure prediction models. Tornado implements a "super-grammar" that includes the standard thermodynamic model as a special case. It can be used to build simpler or more complex models with fewer or more parameters, and it can be used to compare thermodynamic, probabilistic, and discriminative parameterization approaches. This is the maintained (up-to-date) version of the software that accompanied Elena's paper "A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more."
Author: Elena Rivas
A prototype noncoding RNA genefinder, based on comparative genome sequence analysis.
This is the code from Elena Rivas that accompanies the paper Noncoding RNA gene detection using comparative sequence analysis. QRNA uses comparative genome sequence analysis to detect conserved RNA secondary structures, including both ncRNA genes and cis-regulatory RNA structures.
Author: Elena Rivas
Experimental code demonstrating a dynamic programming algorithm for RNA pseudoknot prediction.
This is experimental code from Elena Rivas, demonstrating a dynamic programming algorithm for globally optimal RNA pseudoknot prediction. The algorithm is discussed in the paper A dynamic programming algorithm for RNA structure prediction using pseudoknots.
Author: Elena Rivas
Maximum likelihood phylogenetic inference, including insertions/deletions.
erate is an extension of Joe Felsenstein's DNAML program which treats insertions and deletions as evolutionary events, rather than ignoring them as missing data (which is what the most widely used phylogenetic inference programs all do). This is the software that accompanied Elena's paper "Probabilistic Phylogenetic Inference with Insertions and Deletions."
Author: Elena Rivas
Experimental code for a structural RNA genefinder: it doesn't actually
work well, because it turns out that structural RNAs don't have much
more secondary structure content than random sequence.
This is
the code from Elena Rivas that goes with the paper Secondary
structure alone is generally not statistically significant for the
detection of noncoding RNAs by Elena Rivas and Sean
Eddy. As the title indicates, the genefinder doesn't work (though we
still think the algorithm is cool), because real RNAs don't generally
have any more secondary structure content than random sequence,
contrary to what we expected. The code will only be of interest to
people trying to reproduce our negative results, or trying to
understand the genome-scanning SCFG alignment algorithm that it
implements.