This repository contains a C++ implementation of a dynamic programming algorithm
for RNA secondary structure prediction. This algorithm is designed to take
additional position-wise signals into account. The novelty of our approach is
that we use a machine-learning method similar to support vector machines in
order to estimate all necessary parameters needed for structure prediction only
from the given RNA data and experimental data coming from chemical modifications
techniques such as SHAPE and similar methods. The only assumption about the
additional signal is that it is correlated with the positions of base pairs of
the molecule.
See INSTALL for (generic) installation instructions.
This is not an official Google product
This repository contains a C++ implementation of a dynamic programming algorithm for RNA secondary structure prediction. This algorithm is designed to take additional position-wise signals into account. The novelty of our approach is that we use a machine-learning method similar to support vector machines in order to estimate all necessary parameters needed for structure prediction only from the given RNA data and experimental data coming from chemical modifications techniques such as SHAPE and similar methods. The only assumption about the additional signal is that it is correlated with the positions of base pairs of the molecule.
See INSTALL for (generic) installation instructions.