Package: imp-dev
Priority: optional
Section: libdevel
Installed-Size: 7938
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.8.0-1
Depends: imp (= 2.8.0-1), 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_2.8.0-1_amd64.deb
Size: 1631946
MD5sum: 77681187987be63997cf018eadc36fbd
SHA1: 8e92253b4362a3fb1f815af006cdaa3276df3956
SHA256: 9169eaad9b7524c0ed5b37d73195a3c05bf7fa9db8860711cbbf1e992478aca7
SHA512: 1980a23fa7d331420b01eaa20573727994e4fc22f5b5fd99cf10b9e8557ee62155434eb7db0380541aca0627695f5b75512e43d186d2d193b55f2e2ff334d94a
Description: The Integrative Modeling Platform
 Headers to compile against IMP.
Homepage: https://integrativemodeling.org/

Package: imp-python3
Priority: optional
Section: libs
Installed-Size: 54123
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.8.0-1
Depends: imp (= 2.8.0-1), python3, python3-numpy
Filename: precise/imp-python3_2.8.0-1_amd64.deb
Size: 13360592
MD5sum: 84dd04c53ea82b65e0e1a0e96e4b12cc
SHA1: 4ab3fc6c8b15d74e3a1c9301e958ec231d790aec
SHA256: 4ce22eeff777d63b798caaad37fa62c1486eb43dbd13678fffe39145e49e3471
SHA512: 58c29fd208d2c5c14b876d93dd827f9f6d9212a4b63a1aaa591c1ce3c3828bf06f12384ad0a97874860d18ec281ac73c4e106aa21ab97d6beff3a634fcd1737b
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: 326803
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Version: 2.8.0-1
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_2.8.0-1_amd64.deb
Size: 65587214
MD5sum: 6e4b912c01778203bbf25eef28233489
SHA1: e47b8abd7dd8fc45eac9e26d8c96aa2867068e73
SHA256: 9d57190f73a933fa56143f53a4c893a762e457df829cec16a516b618ce777d9d
SHA512: 2c29f9cd641c9e732837444e9635fb5c6dfbe66ca973ea11c1939da3e546ea280a4efa9a888c3352b2128128ce77a5f53b2c1e2f6721504d46499cd36bfa3423
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/