Package: imp-dev
Priority: optional
Section: libdevel
Installed-Size: 7631
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.6.2-1
Depends: imp (= 2.6.2-1), 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_2.6.2-1_amd64.deb
Size: 1109802
MD5sum: 987c0f5ce13fa444cecf22ce3eaed6cc
SHA1: 809fe5d1b59467b9a8efa42211c65e16e6d0d3ee
SHA256: a85a72b38f9a08dde1964678ef95e3636d41235bcb4096f453cdf3225f2ed4c0
SHA512: 1dfb6fb2edaf6b0053a3ad770dba519fce7b85aae5f852af2b268281e52417642e7503212c162a61c10f716cbcd0542155b47daaef0c7706895516417abda6c5
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: 2.6.2-1
Depends: imp (= 2.6.2-1), python3, python3-numpy
Filename: trusty/imp-python3_2.6.2-1_amd64.deb
Size: 7764844
MD5sum: 7b69ebbcf6fce2f09349b18dec77ec9a
SHA1: 34ecd120e49e1451e243f07f6d9d574f4c6d9747
SHA256: d8e9bbc4bb2c5e08061046c9e84d27deb51f6e04d6d1f93e8181638b23806f9d
SHA512: a7170603836dcd60cbbf323c797f03fac4d88f56b2722801797074278079edb4fd03284f7316bb1b2824018bb5ec5277eabb859595c3c492af3eccc79cbb693c
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: 327621
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Version: 2.6.2-1
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_2.6.2-1_amd64.deb
Size: 38629530
MD5sum: 8825088fb958b82201f7a9607f004f6c
SHA1: fd9ed50b5911c774f8902b97586a632b3fb33966
SHA256: 4e431312d9f9b9cad1dd469bd6284d569992891118ebe08f0e821b655158b49d
SHA512: 23927b080c7a7d8cfa711d05a1dbda49f64df641cca1363ce2ec3323deba40a206dbd0301d48c2ed9e532ee89e84dd01e93d4e76b60b22d183e4ea693015ab9d
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/