hmm_smooth

This feature smooths the HMM matrix \(H\) by using sliding window of length \(sw\) to incorporate information
from up and downstream residues into each row of the HMM matrix. Each HMM row \(r_i\) is made into the summation
of \(r_{i-(sw/2)}+... r_i...+r_{i+(sw/2)}\), for \(i = 1:L\), where \(L\) is the number of rows in \(H\).
For rows such as the beginning and ending rows, \(0\) matrices of dimensions \(sw/2, 20\) are appended to the
original matrix \(H\).

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_smooth function

<dl><dt>hmm</dt>
<dd>The name of a profile hidden markov model file.</dd>
<dt>sw</dt>
<dd>The size of the sliding window.</dd></dl>

Arguments

hmm_smooth — hmm_smooth

<dl>

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


<dt>sw</dt>
<dd>The size of the sliding window.</dd>

</dl>

hmm_smooth: hmm_smooth

Description

Usage

Value

Arguments

References

Examples