Experimental Inferential Structure Determination
Copyright (c) 2016, Teresa Head-Gordon and David Brookes All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of UC Berkeley nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL Teresa Head-Gordon BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
This repository contains an implementation of the procedures outlined in J. Am. Chem. Soc., 2016, 138 (13), pp 4530–4538.
Please read the online documentation at http://davas301.github.io/eisd/ for more information and contact david.brookes@berkeley.edu with any questions.
This program relies (or has relied in the past) on the SciPy, Scikit-learn, MMTK, and Biopython libraries, and uses the external program SHIFTX2. These are cited in order below:
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Jones E, Oliphant E, Peterson P, et al. SciPy: Open Source Scientific Tools for Python, 2001-
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Scikit-learn: Machine Learning in Python, Pedregosa et al., JMLR 12, pp. 2825-2830, 2011.
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Konrad Hinsen The Molecular Modeling Toolkit: A New Approach to Molecular Simulations J. Comp. Chem. 21, 79-85 (2000)
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Peter J.A Cock, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics (2009) 25 (11): 1422-1423
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Beomsoo Han, Yifeng Liu, Simon Ginzinger, and David Wishart. "SHIFTX2: significantly improved protein chemical shift prediction". Journal of Biomolecular NMR, 2011, 50 (1), pp 43-57.