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-dev, libfftw3-dev, libopencv-dev, libgsl0-dev, python-dev, libann-dev
Filename: trusty/imp-dev_2.6.1-1_amd64.deb
Size: 1109696
MD5sum: b6161082cfc756f2819b56070244b8ad
SHA1: 3cad98d9ed66e6be1873b5ada8fb9af1de6bbd77
SHA256: d239300aac38091eeff1960041abd6dd2146507426aa6181e04ddb50c0478239
SHA512: 3d609e8de1d1ae4b34c80e8c0978356435539ffc59e978aba3426f0ef224a2b575eb1bf366abc542ab7f72a48fa6e417e12de06fca05b69616187e6d470ec1c0
Description: The Integrative Modeling Platform
 Headers to compile against IMP.
Homepage: https://integrativemodeling.org/

Package: imp-python3
Priority: optional
Section: libs
Installed-Size: 56285
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: trusty/imp-python3_2.6.1-1_amd64.deb
Size: 7765182
MD5sum: 5c9a685b94bbf7e2ebafee3f1f0b259d
SHA1: dd4f49b0613f4448dd19a6f44c6dcbcde0d161fd
SHA256: 3aefccdc97936ae5f1ee3ed1c87518b6fee4305b2b0cf6ce6abd8fc262fc8585
SHA512: ffb84de3f27c5aa88b83cfb2a78f30dc3ae56b82d303f7e0ff5cb5906e3949cd87552f3782a23c4a64e8cd9b14f5f73285d3a43f5a7ceb26410df7ed4f035841
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: 327611
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Version: 2.6.1-1
Depends: libboost-filesystem1.54.0, libboost-graph1.54.0, libboost-iostreams1.54.0, libboost-program-options1.54.0, libboost-random1.54.0, libboost-system1.54.0, libboost-thread1.54.0, libc6 (>= 2.14), libcgal10, libfftw3-double3, libgcc1 (>= 1:4.1.1), libgmp10, libgomp1 (>= 4.4), libgsl0ldbl (>= 1.9), libhdf5-7, libmpfr4 (>= 3.1.2), libopencv-core2.4, libopencv-highgui2.4, libopencv-imgproc2.4, libstdc++6 (>= 4.6), python-numpy
Filename: trusty/imp_2.6.1-1_amd64.deb
Size: 38673460
MD5sum: cd0b8668611b69796a890f87e7d55254
SHA1: e3c2ca182bd0cc620f23d0e7885f540fbb422033
SHA256: 7927fb3749f1e11de7c43427dab281da32fb1b803a2b744aad512ce8142a9b35
SHA512: 961b31356eadc0474d2fc8c92f6d96f833755aaa700cb13a5f641ef709f4ab00a8319e44676b93dd2498c29a906096d26de118d7978d3892f28448068a0d71e5
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/