Modeling Biological Sequences using Hidden Markov Models

The hidden Markov models are applied in different biological sequence analysis. For example, hidden Markov models have been used for predicting genes. If we have a new sequence and we want to identify the genes inside that sequence, we can use hidden Markov models to annotate the regions first and then identify the location of a gene. Hidden Markov models can provide very good genetic models for performing different dynamic alignment algorithms for pairwise as well as multiple sequence alignment. We can also use hidden Markov models for building a profile for a sequence family, base calling, determining DNA sequencing errors, prediction of the secondary structure of protein, identifying copy number variations and many more. In other words, hidden Markov models are very important mathematical models that have been applied in various biological sequence analysis.

[kellythayer]

I'd be very interested in seeing a video about how to implement a profile HMM using multinomial profile HMM in scikit learn. If you have such a video please send the link!

[LordBurningStuff]

Let me be the first. Great video, well explained for a lay man like me.