This project was performed pursuant to Baylor College of Medicine Grant No. DBI-054795 from the National Science Foundation. Lydia Kavraki has also been supported by a Sloan Fellowship. The computers used to carry out experiments for this project were funded by NSF CNS 0454333 and NSF CNS-0421109 in partnership with Rice University, AMD and Cray.
We are indebted to Dr. Slava Fofanov and Dr. Marek Kimmel from the Statistics Department at Rice University for their contributions to the statistical analysis and for their comments on LabelHash. We are also deeply grateful for the help of Dr. Brian Chen with MASH and the earlier contributions of Dr. Olivier Lichtarge, Dr. David Kristensen and Dr. Andreas Martin Lisewski within the context of the above mentioned NSF funded project.
LabelHash includes code related to proximity data structures and coordinate transformations from the OOPSMP package, which is also developed by our group. LabelHash relies on several external programs and libraries: CMake, Boost, Open MPI, HDF5, msms, fftw3, LAPACK, zlib, Chimera, and python. We use a code fragment from the Quaternion Characteristic Polynomial method, an extremely fast technique for computing the optimal LRMSD alignment. The ViewMatch plugin uses the PDB-to-GO mapping from the Jena Library, the PDB-to-EC mapping from PDBSProtEC, and relies on the PDBsum server for additional protein information. This documentation was generated using Doxygen, using this CSS framework for the drop-down menus and the Blueprint CSS framework for general formatting.