hmm_distance {protHMM}

hmm_distance

Description

This feature calculates the cosine distance matrix between two HMMs A and B before dynamic time warp is applied to the distance matrix calculate the cumulative distance between the HMMs, which acts as a measure of similarity, The cosine distance matrix D is found to be D[a_i, b_j] = 1 - \frac{a_ib_j^{T}}{a_ia_i^Tb_jb_j^T}, in which a_i and a_i refer to row vectors of A and B respectively. This in turn means that D is of dimensions nrow(A), nrow(b). Dynamic time warp then calculates the cumulative distance by calculating matrix C[i, j] = min(C[i-1, j], C[i, j-1], C[i-1, j-1]) + D[i, j], where C_{i,j} is 0 when i or j are less than 1. The lower rightmost point of the matrix C is then returned as the cumulative distance between proteins.

Usage

hmm_distance(hmm_1, hmm_2)

Arguments

hmm_1

The name of a profile hidden markov model file.

hmm_2

The name of another profile hidden markov model file.

Value

A double that indicates distance between the two proteins.

References

Lyons, J., Paliwal, K. K., Dehzangi, A., Heffernan, R., Tsunoda, T., & Sharma, A. (2016). Protein fold recognition using HMM–HMM alignment and dynamic programming. Journal of Theoretical Biology, 393, 67–74.

Examples

h<- hmm_distance(system.file("extdata", "1DLHA2-7", package="protHMM"),
system.file("extdata", "1TEN-7", package="protHMM"))