This is a test version of Biostars. For the public version, visit https://www.biostars.org.
Amino Acid Propensity In A Gapped Data

Hi,

I am trying to calculate the propensity of amino acids in the beta-strands of my data-set. The problem with my data-set is that strands are of different length . For eg

There are strands like this :- ABCDG KJLIJ GBAHUUJKI BHAJYJKIIO

Considering the above case, there is no problem in calculating the propensity till the 5th position of the strand from the N-ter. The problem starts from the sixth position as the first two strands do not have any more residues.

I hope I have made my point clear. Can anybody help me out ??

• 2,516 views • link
updated by Biostar Biostar • written by bharat.85.monu • bharat.85.monu

This question is not very clear. You mean that there are 4 different strands; the first two contain 5 residues, the third 9 and the fourth 10 residues? Also I think you mean "frequency", not "propensity".

• 0 views • link
written by Neilfws Neilfws

1 answer

Is this what you are looking for?

import re
strands=["ABCDG","KJLIJ","GBAHUUJKI","BHAJYJKIIO"]
for strand in strands:
    seen=[]
    results=[]
    results.append(strand)
    for x in strand:
       if x not in seen:
            seen.append(x)
            n=len(re.findall(x,strand))
            results.append(x)
            results.append(n)
    print results

You can run this in python (check the indentation when copy/pasting). For each strand it prints a list counting each AA in each "strand" hope this helps

• 2 views • link
written by Whetting Whetting

Log in to answer this question.

More posts like this