Package: imp-dev
Architecture: amd64
Version: 2.6.2-1
Priority: optional
Section: libdevel
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 8354
Depends: imp (= 2.6.2-1), cmake, swig, libboost-filesystem-dev, libboost-graph-dev, libboost-iostreams-dev, libboost-program-options-dev, libboost-random-dev, libboost-regex-dev, libboost-thread-dev, libcgal-dev, libcgal-qt5-dev, libhdf5-dev, libfftw3-dev, libopencv-dev, libgsl0-dev, python-dev, libann-dev
Filename: xenial/imp-dev_2.6.2-1_amd64.deb
Size: 1109438
MD5sum: 6373adbd87d681c8ddf7f7effdde2532
SHA1: ddf6956f4a87b92019105046e24168c02dcf1b2f
SHA256: 41423c84c45c9c2e3cdb759ef0d574edb5f61442962497b63df8afb1b01afb45
SHA512: b91541a8323d9ffce063245301b5709dd6bb96fdc39e5fa2b0b42f4ac56b77b738cc6ef722854717a89f3749bacdb8fe7368b94dc246c20b7c0a729699c0e621
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Headers to compile against IMP.

Package: imp-python3
Architecture: amd64
Version: 2.6.2-1
Priority: optional
Section: libs
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 57876
Depends: imp (= 2.6.2-1), python3, python3-numpy
Filename: xenial/imp-python3_2.6.2-1_amd64.deb
Size: 7935744
MD5sum: df330f0265568fb0d24bd31c1eaff45f
SHA1: 9281fa97f687abdf85043a275226d63d6a7c5de0
SHA256: aebef2189174a83c2436fe2889917bd0873688378b6e688bebf753f0fc159567
SHA512: 058ac2663caeca712c38a6f47fa39cd8ce95b2ef5da92f246c456bde7d5bcba4725062a1cb0df994e3c950e238bdb98e65a3dcae0a68a42c124f200d76cdf456
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Wrappers for Python 3 (the base IMP package contains Python 2 wrappers).

Package: imp
Architecture: amd64
Version: 2.6.2-1
Priority: optional
Section: libs
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 331657
Depends: libboost-filesystem1.58.0, libboost-graph1.58.0, libboost-iostreams1.58.0, libboost-program-options1.58.0, libboost-random1.58.0, libboost-system1.58.0, libboost-thread1.58.0, libc6 (>= 2.14), libcgal11v5, libfftw3-double3, libgcc1 (>= 1:4.0), libgmp10, libgomp1 (>= 4.9), libgsl2, libhdf5-10, libmpfr4 (>= 3.1.3), libopencv-core2.4v5, libopencv-highgui2.4v5, libopencv-imgproc2.4v5, libstdc++6 (>= 5.2), python-numpy
Filename: xenial/imp_2.6.2-1_amd64.deb
Size: 39049014
MD5sum: f06c65a65b28ab108938014f753998a9
SHA1: 5aa05448e26076104a32b03af97d348237c0173d
SHA256: 01b79d6a9293abfe7592ccc4fba53d9fe3bb452bab5a39a73be827e38bc90469
SHA512: 579490d231d6cb9aa5a7f0369720ca6ccf96f44f9161f4427ac66d6fe87fe01b198a4ecb731430a2fda6ff2eade673b5a82fec51453e67cec9b0d53ee13ef731
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
  IMP's broad goal is to contribute to a comprehensive structural
  characterization of biomolecules ranging in size and complexity from small
  peptides to large macromolecular assemblies. Detailed structural
  characterization of assemblies is generally impossible by any single existing
  experimental or computational method. This barrier can be overcome by hybrid
  approaches that integrate data from diverse biochemical and biophysical
  experiments (eg, x-ray crystallography, NMR spectroscopy, electron microscopy,
  immuno-electron microscopy, footprinting, chemical cross-linking, FRET
  spectroscopy, small angle X-ray scattering, immunoprecipitation, genetic
  interactions, etc...).
  .
  We formulate the hybrid approach to structure determination as an optimization
  problem, the solution of which requires three main components:
    * the representation of the assembly,
    * the scoring function and
    * the optimization method.
  .
  The ensemble of solutions to the optimization problem embodies the most
  accurate structural characterization given the available information.
  .
  We created IMP, the Integrative Modeling Platform, to make it easier to
  implement such an integrative approach to structural and dynamics problems.
  IMP is designed to allow mixing and matching of existing modeling components
  as well as easy addition of new functionality.