Hello to all, I'm a computer science student and I do not know anything about chemistry and bioinformatics ... I have to build a neural network that, starting from the secondary structure of proteins, preaches "solvent accessibility". My starting dataset is this: http://www.princeton.edu/~jzthree/datasets/ICML2014, but my professor told me to also use dssp ... that I have no idea what it is and what it is for. . Can anyone tell me how to get the "solvent accessibility" from the dataset alone? Do I need to get PDB files first and then convert to DSSP?
Excuse my ignorance on the subject, but I am a novice. Thanks in advance.
Ok thanks! Another question: how can i (if i can) link the entries in the others db (es. cullpdb+profile_6133.npy.gz) with the pdbs files?
I think it is written in the paper. (This one http://proceedings.mlr.press/v32/zhou14.html ? I'm not sure cuz I haven't read it.)
There are many papers about Secondary Structure or Solvent Accessibility prediction. https://scholar.google.co.jp/scholar?as_ylo=2005&q=secondary+structure+prediction+-RNA+-server Material & Methods section in those papers will be helpful.