Package: imp-dev
Priority: optional
Section: libdevel
Installed-Size: 7845
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.7.0-1
Depends: imp (= 2.7.0-1), 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, libhdf5-serial-dev, libfftw3-dev, libopencv-dev, libgsl0-dev, python-dev, libann-dev
Filename: precise/imp-dev_2.7.0-1_amd64.deb
Size: 1613440
MD5sum: 0f7c0976e20be0120abf4cf63e562eab
SHA1: 25e1263e20e371ea8055a5bf0a09288131ff0179
SHA256: 2db8d1dd10b5d0da1bd5260cb8daf8aec2377dbb9dd393ef1edcce972a98a29b
SHA512: 0edcfdb20d96ddcedba170c2f39a284202426ebd0383fdfdb8a806b7c0e7ae47bd534be56e61a470b255b80047b7f3a250d9cc4847f8500608a57e70a5b1ce9c
Description: The Integrative Modeling Platform
 Headers to compile against IMP.
Homepage: https://integrativemodeling.org/

Package: imp-python3
Priority: optional
Section: libs
Installed-Size: 55854
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Source: imp
Version: 2.7.0-1
Depends: imp (= 2.7.0-1), python3, python3-numpy
Filename: precise/imp-python3_2.7.0-1_amd64.deb
Size: 14107982
MD5sum: ffcf6163fe6daa97f6dc26b8c878fd09
SHA1: e569e3471e9ce5a74e3aec8505378901584e946d
SHA256: 5cf3befd3795a50931eb3e134b19aa0ec641142726fff5b9daa553f6360b4697
SHA512: 32612b5226b95d27b285f73ea899e08f0be6ab0c71a0b8ca25493a2d26741af59f8d0c38aab65f1bceb67c78ab3ca03333702f92d0fed5bb609e870833d02575
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: 328460
Maintainer: Ben Webb <ben@salilab.org>
Architecture: amd64
Version: 2.7.0-1
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_2.7.0-1_amd64.deb
Size: 66351050
MD5sum: 2c5dbf595c40067c8e70de658e9fb1cc
SHA1: 779e4e846057f11d9c114385c6eb20aa9a18bf99
SHA256: ed49b81ff5958f1e557db11f50c5a0fb8e082602907782ed2a4bf9055b4bf862
SHA512: 8e73987cc1b3657f34a6624f2db2b250c9b945d1102ca84a20bc188f56eed9f274b57ca84415dcdbb8d358eced7d68507776ffbb6f5df29c0574802b06b2af62
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/