This github repository contains code, docked models and data pertaining to results described in "Computational epitope binning reveals functional equivalence of sequence-divergent paratopes".
License: GNU General Public License v3.0
Python 100.00%
epibin's Introduction
# ******************************************************************************
# Authors : Jarjapu Mahita
Dong-Gun Kim
Sumin Son
Yoonjoo Choi ([email protected])
Hak-Sung Kim ([email protected])
Chris Bailey-Kellogg ([email protected])
# Project : Computational epitope binning reveals functional equivalence of sequence-divergent paratopes
# Description : This github repository contains code, docked models and data pertaining to results
described in "Computational epitope binning reveals functional equivalence of sequence-divergent paratopes".
# ************************************************************************
# Copyright (C) <2021> <Jarjapu Mahita>
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
#**************************************************************************
#******SOFTWARE REQUIREMENTS (VERSION)*************
1. Python 3 and above
2. BioPython (compatible with Python 3, 1.79)
3. Pandas (1.2.1)
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#***********INSTRUCTIONS FOR REPRODUCING EPIBIN RESULTS DESCRIBED IN PAPER**************************
Each of the 'Antibodies' and 'Rebebodies' folders contains a sub-folder named 'example' within which sub-folders along with instructions about executing the code to reproduce the output are present.
In addition to the 'example' sub-folder, there are other sub-folders each of which contains a README file describing the types of files and scripts used to generate the Epibin results.
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Hello,
Great thanks for sharing the code and data for your paper, which is really valuable to the community. I am wondering if you also can provide the antibody experimental competition label data, which were used to compute AU-PRC?
I understand "The experimental data for the antibody studies was obtained from the supplementary material of the respectively cited publication" mentioned in the paper. It is not-trivial to get that binary label in order to reproduce the result.