hmm_ac

This feature calculates the covariance between two residues separated by a lag value within
the same amino acid emission frequency column along the protein sequence.

Calculates a comprehensive list of features from profile hidden Markov models (HMMs) of proteins.
Adapts and ports features for use with HMMs instead of Position Specific Scoring Matrices, in order to take
advantage of more accurate multiple sequence alignment by programs such as 'HHBlits' Remmert et al. (2012)
<DOI:10.1038/nmeth.1818> and 'HMMer' Eddy (2011) <DOI:10.1371/journal.pcbi.1002195>. Features calculated by
this package can be used for protein fold classification, protein structural class prediction,
sub-cellular localization and protein-protein interaction, among other tasks. Some examples of features
extracted are found in Song et al. (2018) <DOI:10.3390/app8010089>, Jin & Zhu (2021) <DOI:10.1155/2021/8629776>,
Lyons et al. (2015) <DOI:10.1109/tnb.2015.2457906> and Saini et al. (2015) <DOI:10.1016/j.jtbi.2015.05.030>.

Shayaan Emran

protHMM

Protein Feature Extraction from Profile Hidden Markov Models

hmm_ac function

<dl><dt>hmm</dt>
<dd>The name of a profile hidden markov model file.</dd>
<dt>lg</dt>
<dd>The lag value, which indicates the distance between residues.</dd></dl>

Arguments

hmm_ac — hmm_ac

<dl>

<dt>hmm</dt>
<dd>The name of a profile hidden markov model file.</dd>


<dt>lg</dt>
<dd>The lag value, which indicates the distance between residues.</dd>

</dl>

hmm_ac: hmm_ac

Description

Usage

Value

Arguments

References

Examples