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: bionic/imp-dev_2.11.0-1_amd64.deb
Size: 719596
MD5sum: aab99427d54dff4050fee3a93f3cb798
SHA1: e3e897be1b5c7ecc484977f9aac8b44b30949d7e
SHA256: 7807650654f24c44968664e08269400a59ddc38639fc1c6d0db5433b4b850f67
SHA512: e7d0b1579472ce899132cf831d2a0e216af2b5c1027035a006210794e10c8700cfde1548a05c183400da102574e21dd65b948b3dfe18522376632393722d26d8
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: 63941
Depends: imp (= 2.11.0-1), python3, python3-numpy, python3-protobuf
Filename: bionic/imp-python3_2.11.0-1_amd64.deb
Size: 8870412
MD5sum: e32e4209d89f6a4f47421797798f12f8
SHA1: 5f9290daa9239b4935a4433b60d1a39abe2a64a0
SHA256: 13ddcdc9084b5115db2a4e75083245049fb38d6bb14dde5334b4bb9b44a3bb5b
SHA512: 814b6cc027dca017141b552fa7dd64af6f610f0eced5571f98ae4039678763cd1d11aee9f9472b325955ac8e6309da6e24378eac9e4eed113023bbc8a8c8dba0
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: 414503
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_2.11.0-1_amd64.deb
Size: 46053544
MD5sum: d9f251ec86fa54a2b17ad7d65801fe0c
SHA1: b8e2b9c850ab8083f629a44c258042cc5f3549d0
SHA256: 62075bf9d9653301a652617343cde3dac1deabd69a1a02f88a958c87cba66998
SHA512: da1d0920d754566dd0cb47d932dcd035447650b1431b48526b4f680ecabc861457332db4a1632c5f237d01d33a354276e4069dc2e89b031988d3e3b6bf1c0abb
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.