My end goal is a C++ implementation of
- a Profile HMM (a profile hidden markov model is a model which contains information about a multiple sequence alignment of proteins; just providing some background as the type of model is not necessarily important for what I want to ask).
- Baum Welch training (and implicitly Forward algorithm, Backward algorithm)
I have everything up and running as long as I don't try to use any silent states.
My biggest problem is that I do not know how to account/modify equations for silent states in my Forward/Backward algorithms. I didn't really find any good examples of this particular case online and I was wondering if anybody could give me a hint or point me in the right direction as I am not very math/stat savvy.
Follow up question: is there a user friendly package/toolbox with these algorithms already implemented? I ask this so that after I manage to complete my algos I can compare results to make sure I compute everything correctly.
I apologize if I was a bit incoherent about my problem. I will be monitoring this question and I will provide additional details as required.
