Package: imp-dev
Priority: optional
Section: libdevel
Installed-Size: 7631
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.6.1-1
Depends: imp (= 2.6.1-1), 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, libhdf5-serial-dev, libfftw3-dev, libopencv-dev, libgsl0-dev, python-dev, libann-dev
Filename: precise/imp-dev_2.6.1-1_amd64.deb
Size: 1560588
MD5sum: ad90832a3c5f4816fb269f8a561c9382
SHA1: 459ce2b38f6153506c6499502fe8fe3df2d7f395
SHA256: 45832e2fd6f2a1bfa385e364a9caa7b9300fed84efd37fbf25e439b723fdd1d8
SHA512: 6e2d06f30ad661bd4a364a23e2652245d00bf4052df869d3d5b86a43b01787bdc25cbee3fd4fcd6593d0151e33ddf666d2e8082dd2a6057c70b08fb2fa02050c
Description: The Integrative Modeling Platform
 Headers to compile against IMP.
Homepage: https://integrativemodeling.org/

Package: imp-python3
Priority: optional
Section: libs
Installed-Size: 54744
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.6.1-1
Depends: imp (= 2.6.1-1), python3, python3-numpy
Filename: precise/imp-python3_2.6.1-1_amd64.deb
Size: 13856418
MD5sum: 7cdb01340b212234ce48ac4b8880be28
SHA1: 86f13a0e37aabf690aaccaf2977d02edde4626ef
SHA256: 4d010593932ca75d9520701ead3e0793bb10db583c9a0fc1764090b20cd5e298
SHA512: 2a0ab1488b3fa657a5b389aebe927d23744c3ef11f642d90eaf0d42194683473fbbd7ad9e24855492501a2d47a25e3f406ebb1c553661efac80514c5e28b223e
Description: The Integrative Modeling Platform
 Wrappers for Python 3 (the base IMP package contains Python 2 wrappers).
Homepage: https://integrativemodeling.org/

Package: imp
Priority: optional
Section: libs
Installed-Size: 326881
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Version: 2.6.1-1
Depends: libboost-filesystem1.46.1 (>= 1.46.1-1), libboost-graph1.46.1 (>= 1.46.1-1), libboost-iostreams1.46.1 (>= 1.46.1-1), libboost-program-options1.46.1 (>= 1.46.1-1), libboost-random1.46.1 (>= 1.46.1-1), libboost-system1.46.1 (>= 1.46.1-1), libboost-thread1.46.1 (>= 1.46.1-1), libc6 (>= 2.14), libcgal8, libfftw3-3, libgcc1 (>= 1:4.1.1), libgmp10, libgomp1 (>= 4.4), libgsl0ldbl (>= 1.9), libhdf5-serial-1.8.4 | libhdf5-1.8.4, libmpfr4 (>= 3.1.0), libopencv-core2.3, libopencv-highgui2.3, libopencv-imgproc2.3, libstdc++6 (>= 4.6), python-numpy
Filename: precise/imp_2.6.1-1_amd64.deb
Size: 65914280
MD5sum: a8609261d703cafece0799681168cca9
SHA1: f3f37c55786e019ecdecd9a2a754dcf7c5b00b8f
SHA256: 456d2d93b9db7e392211886a4cc2df5b69c4f01d4f1186d484787ab1e3d481fd
SHA512: 601d3253187dd14a303967cbae7748eb7d0bda39550f325fb1c47abba13ba1c9f05dee94b56ba7906aa2d097c51d1798079e3c0ca88eae95a007270f326140ed
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.
Homepage: https://integrativemodeling.org/