fp_hmm

This feature consists of two vectors, \(d, s\). Vector \(d\) corresponds to the sums across the sequence
for each of the 20 amino acid columns. Vector \(s\) corresponds to a flattened matrix \(S[i, j] = \sum_{k = 1}^{L}
H[k, j] \times \delta[k, i]\) in which \(\delta[k, i] = 1\) when \(A_i = H[k, j]\). \(A\) refers to a list of
all possible amino acids, \(i, j\) span from \(1:20\).

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

fp_hmm function

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

Arguments

fp_hmm — fp_hmm

<dl>

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

</dl>

fp_hmm: fp_hmm

Description

Usage

Value

Arguments

References

Examples