Welcome to the ssHMM documentation! =================================== ssHMM stands for "Sequence-Structure Hidden Markov Model". It is an RNA motif finder and recovers sequence-structure motifs from RNA-binding protein data. Background ---------- RNA-binding proteins (RBPs) play a vital role in the post-transcriptional control of RNAs. They are known to recognize RNA molecules by their nucleotide sequence as well as their three-dimensional structure. ssHMM combines a hidden Markov model (HMM) with Gibbs sampling to learn the joint sequence and structure binding preferences of RBPs from high-throughput RNA-binding experiments, such as CLIP-Seq. The model can be visualized as an intuitive graph illustrating the interplay between RNA sequence and structure. Scope ----- ssHMM was developed for the analysis of data from RNA-binding assays. Its aim is to help biologists to derive a binding motif for one or a number of RNA-binding proteins. ssHMM was written in Python and is a pure command-line tool. License ------- The project is licensed under the GNU General Public License. .. toctree:: :maxdepth: 2 :caption: Contents: Installation/index tutorial Output/index preprocess Reference/index GitHub