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-serial-dev, libfftw3-dev, libopencv-dev, libgsl0-dev, python-dev, libann-dev
Filename: precise/imp-dev_2.6.2-1_amd64.deb
Size: 1560666
MD5sum: 653d05e63aca6a307be6b82e8f3a0f1a
SHA1: 88b7e41b19dcea23851c67634f07dfb6f8470db7
SHA256: 314ca28c8ad71c641ec8216ca501ade6db20c294477fe917110ab8c72e042a1c
SHA512: c621e3a71356ce09c66ddbf2a7847070328dbd4f78853a9498bdb667821723e08b4eb3e8bbdc5ead1b03921e1ea8468b4f0ab8b10353f3435e7168f7d3210893
Description: The Integrative Modeling Platform
 Headers to compile against IMP.
Homepage: https://integrativemodeling.org/

Package: imp-python3
Priority: optional
Section: libs
Installed-Size: 54744
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: precise/imp-python3_2.6.2-1_amd64.deb
Size: 13856782
MD5sum: a41ed3f62a2848258a301fa725cb9abe
SHA1: 6eb1678d7e5fab241f1e22c876d9bb606c5f5390
SHA256: 311cffa861664e9ca5d6b58129de01994c5021df650678201373a52eaf7ad225
SHA512: a72c9162aa4b4276893a0594547646785e1cf94cdbaedf657e8c575687e3ff9e2e8bd797c9c6ebe7de929b09e7fbcbf8ec6e6821c5cd2bfefadac27d1a7f2c3f
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: 326882
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Version: 2.6.2-1
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_2.6.2-1_amd64.deb
Size: 65914022
MD5sum: e1b95bdc447a64c92956906e4b385817
SHA1: a75b470408a2dc057dc48e1ae0b6c260b00fa237
SHA256: 04c5d92c0b9f7e555dc4ad2f49f260860f4fcb4e3f6064a1e9342c5d55a9febd
SHA512: 035b063c0bdafacf643fb5f102ad774c0a212120ef658a8b56a93f10326ff456807a3d6bf7e105cde3fb3d36720a484ca034388e46e0862e9b8b503e8a2d79e2
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/