'Match states' presentation slideshows

Hidden Markov Models

Hidden Markov Models. Fundamentals and applications to bioinformatics. Markov Chains. Given a finite discrete set S of possible states, a Markov chain process occupies one of these states at each unit of time. The process either stays in the same state or moves to some other state in S.

603 views • 40 slides

Usage of profile HMMs in Bioinformatics

490 views • 23 slides

Ch5 Profile HMMs for sequence families

Ch5 Profile HMMs for sequence families. To identify whether a sequence belongs to a family and align it to the other members. Pairwise searching with any of the members may not find sequences distantly related to the ones you have already.

189 views • 18 slides