Package: imp-dev
Architecture: amd64
Version: 2.10.0-1
Priority: optional
Section: libdevel
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 5375
Depends: imp (= 2.10.0-1), 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, libcgal-qt5-dev, libhdf5-dev, libfftw3-dev, libopencv-dev, libgsl0-dev, python-dev, libann-dev, libeigen3-dev, libprotobuf-dev
Filename: bionic/imp-dev_2.10.0-1_amd64.deb
Size: 718596
MD5sum: 0e83c6b874ebab20ce14040578e40d93
SHA1: 4a3d49619b7fee9c6440bfa803c4c224569d6280
SHA256: af415f655ff3c32ea5640d9b6304b4cdb815de99d9dc284a36c19ff581f3f256
SHA512: 4286a1e85af1c3e6274c854e246d0fe60bf3255bb160282df2884c1d8f45b467e6e988e23d1ef8892a160955a3d2a6f9780694d9295303473576e53136a746c3
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Headers to compile against IMP.

Package: imp-python3
Architecture: amd64
Version: 2.10.0-1
Priority: optional
Section: libs
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 63938
Depends: imp (= 2.10.0-1), python3, python3-numpy, python3-protobuf
Filename: bionic/imp-python3_2.10.0-1_amd64.deb
Size: 8855444
MD5sum: 9308d5c99c10300bb9b0de50f68883f4
SHA1: 96c839a7b65de3860919e5f5bf52c6f9a16c2ec9
SHA256: e0817af5356b640114a714ca7f30f98f93ac30624e021974cdf48d601822ceb5
SHA512: 09449b3e1277af11ad93f13c85512124faaf2134459fa7957f294411e560db731ab1ab33090ed2211a69a4dd17449e6f099ea8f3e524cb9951050e0ffec63db4
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: 2.10.0-1
Priority: optional
Section: libs
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 413795
Depends: libboost-filesystem1.65.1, libboost-graph1.65.1, libboost-iostreams1.65.1, libboost-program-options1.65.1, libboost-random1.65.1, libboost-system1.65.1, libc6 (>= 2.27), libcgal13, libfftw3-double3 (>= 3.3.5), libgcc1 (>= 1:4.0), libgmp10, libgomp1 (>= 4.9), libgsl23, libgslcblas0, libhdf5-100, libmpfr6 (>= 3.1.3), libopencv-core3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libprotobuf10, libstdc++6 (>= 5.2), python-numpy, python-protobuf
Filename: bionic/imp_2.10.0-1_amd64.deb
Size: 46072636
MD5sum: 4e2e90a0d7b2a4a043aed4facd659800
SHA1: d98dc0abc68417991f7aaf3b99afdfd402e0ddcf
SHA256: 4e5c638f5d71e2cbac54fb78494a09dd7d26a406a8c78dd91ccb13665134f118
SHA512: 1d37641e8474bc91e6d0803ef5fece21e083d8e14e07fe77867553008bddc317db483f7ec75e4733b3a1216f4d2fc07f506095e13b5a779aae99ae19528ef0b6
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.