Package: imp-dev
Architecture: amd64
Version: 2.11.0-1
Priority: optional
Section: libdevel
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 5383
Depends: imp (= 2.11.0-1), 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: xenial/imp-dev_2.11.0-1_amd64.deb
Size: 724136
MD5sum: f838929a6f97e8139d3b68ba02ab10f7
SHA1: 13570b9ffaf310df1b48a71b8713d3d686b2870c
SHA256: 3bc2d7279a65462d1111669257cb2dcbd2c57e52f7f1c48ac610bbc366f977ca
SHA512: e922dfb18bd5d3221b9b6342c4fd50c77799c9d8e7669776d2e048f89af7b67c1982ff8aa17991cc5d32eef9392832ccf12e8fb8daafc4e8ab1091a736afbea0
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Headers to compile against IMP.

Package: imp-python3
Architecture: amd64
Version: 2.11.0-1
Priority: optional
Section: libs
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 64556
Depends: imp (= 2.11.0-1), python3, python3-numpy
Filename: xenial/imp-python3_2.11.0-1_amd64.deb
Size: 8766060
MD5sum: c149489d74e07b35edeb7758c12fa298
SHA1: a43e6f0abd03f6e3833c938dbf1fb7767a5027a0
SHA256: 534d6c8c657e16d85f7539a574a660a3f5efce30d95e9332694dcf255dcbc6cc
SHA512: d3dfccc6b808f1a689e38cf6ce80e7e908a30b78768f834e0f4816cf63be635e6700cdde89cb949d318ef45fea838c4982e8db49bad33a07bdf12ca5d76bba1c
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: 2.11.0-1
Priority: optional
Section: libs
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 414525
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 (>= 1:3.4), libgmp10, libgomp1 (>= 4.9), libgsl2, libhdf5-10, libmpfr4 (>= 3.1.3), libopencv-core2.4v5, libopencv-highgui2.4v5, libopencv-imgproc2.4v5, libprotobuf9v5, libstdc++6 (>= 5.2), python-numpy, python-protobuf
Filename: xenial/imp_2.11.0-1_amd64.deb
Size: 46935104
MD5sum: b8e47f8e48fa6dc80dc4b51466815d4d
SHA1: 6f4a50efbe1f5deb2b9c5d88e2233aac6c3ca948
SHA256: a4cf40a14f008e21a108ad75c3611bc5bffec506196e6389ae49940b7c21156e
SHA512: 1a73ffce659b809855d5555fc47d48ea9a3c4fb0aa8015b5c383f1cbc5dccbf9dc761c20b2c852ae03e104ab6675fa233313a6be8d6cd94ba479f9bdc5b609a1
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.