leeyang/respre

ResPRE is an algorithm for protein residue-residue contact-map prediction

respre's Issues

feature and labels

Hello, i have two questions hope i get the answers from you

1- first the rule of the sequence alignment is that to extract a chunks of subsequences represents the first sequence

2- and then those alignments are fed to the covariance matrix to extract a matrix called covariance matrix the measures the correlations between each of these alignments with each other

3-from what i understand it that proteins contact map describe the distance matrix as a label , like for example the distance between the first amino acid in the first chain and the first amino acid in the second chain is equal to 200 A, we set a threshold with 8 A so the proteins contact map description for this distance number will be "not in contact" "False" or in binary world "0" is im right with that understanding

My Questions
First
1-what is the rule of the covariance matrix
2- what is the rule of proteins contact map are those the labels of the matrix distances if so what is the rule of the covariance matrix
3- what is the input to the neural network model
A- what is the feature, are those the distance matrix if yes what is the rule of covariance matrix
B- what is the label of these features are Proteins contact map is the labels in (0's and 1's )

Second
1- i want from you kindly to give me a hint or steps which is the first script to use and second and so on cuz i want to cite your paper so i started to inspired from your great work

thanks in advance

test case, precision matrix

Hello,

I was running ResPRE on the given test case, and saved the calculated precision matrix (21L, 21L). This is the precision matrix printed out:

[[14.20261936 0. 0. ... 0. 0. 0. ]
[ 0. 14.20261936 0. ... 0. 0. 0. ]
[ 0. 0. 14.20261936 ... 0. 0. 0. ]
...
[ 0. 0. 0. ... 14.20261936 0. 0. ]
[ 0. 0. 0. ... 0. 14.20261936 0. ]
[ 0. 0. 0. ... 0. 0. 14.20261936]]

It looks like this is just an identity matrix. I was wondering whether this is the correct output (persumably not)? And what might be the issue? I have not modified the code, other than adding one line to save the returned precision matrix.

Thanks,