I'm using Pfam HMMs to identify domains in my *T. cruzi* proteins with the HMMER program.

I kinda understand that a HMM is build by a family multiple sequence alignment, by calculating probabilities of states.

But how the hmmscan works to classify a new protein by families HMMs? Where can I read more about this?
Academic references would be appreciated.
In this context, HMMs are numerical representations of sequence alignments that are more information-rich because both residue substitution patterns and gap penalties are treated in probabilistic fashion. Diverse sequences are given higher weight in HMMs, and they also include background residue probabilities in a way that is inversely proportional to the alignment depth.

If you don't have access to Krogh, Durbin & Eddy book, the PDF version is available [**here**][1]. Any of the early Krogh, Eddy and Karplus papers would be good as starting points.

https://www.ncbi.nlm.nih.gov/pubmed/8744772

https://www.ncbi.nlm.nih.gov/pubmed/9918945

https://www.ncbi.nlm.nih.gov/pubmed/9927713

https://www.ncbi.nlm.nih.gov/pubmed/18075166


  [1]: https://www.semanticscholar.org/paper/Biological-Sequence-Analysis%3A-Probabilistic-Models-Durbin-Eddy/571f5bbecd3a083a2bb6844f59a3f8cea237252e