Package: imp-dev
Architecture: amd64
Version: 2.12.0-1
Priority: optional
Section: libdevel
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 6915
Depends: imp (= 2.12.0-1), 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_2.12.0-1_amd64.deb
Size: 931312
MD5sum: 4e1c16d0638357e5718861cf45cd1e1f
SHA1: d864882346913c011dde8cad766e6021062da72a
SHA256: c0660354972581f4ff285a11a9071f3b485d918fa5880110ba5e7365fb424fa2
SHA512: 5c8c3527d1c8ecd1c58fd6692be7b52d44738bcef63e561c68a7dd7ff7cdd3a124e9b380c916992be7aebac0789ac36bb582e36541bd080596e5c3de65adc2ea
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Headers to compile against IMP.

Package: imp-python3
Architecture: amd64
Version: 2.12.0-1
Priority: optional
Section: libs
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 65730
Depends: imp (= 2.12.0-1), python3, python3-numpy, python3-protobuf
Filename: bionic/imp-python3_2.12.0-1_amd64.deb
Size: 9128500
MD5sum: 09f2e0b5049dc4d176b0fbac5d551ac2
SHA1: cb8f1bc530e527b59948a2fa102f21319f39b72f
SHA256: f73f5a7d0e674414476861c589ef6c0d84373483f8b2722336e149294fe99cf0
SHA512: 09718719afdce3ae76fb8d4a275efdeed495aa7d8fe818de0ea6b4a17ac7f85ab32340eced89e2c06badef2229487bd1ad57942c6691bba74559a91fc18719a8
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: 2.12.0-1
Priority: optional
Section: libs
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 415127
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_2.12.0-1_amd64.deb
Size: 45974064
MD5sum: e09b6e71e26d55df7790a2b1dbfe40d8
SHA1: fc3cfdb36759bd5bd7d24aa0fcef606c7f1e40bc
SHA256: 692c3d75ef6229f42e64077314a6bdb829fa2a28e9c3191e8ba2058df73e1c54
SHA512: 03675d058d1a3edede0d804aaf41bce56b6d3d5cee67cc1cd3bfbad55ad5e907341560cfccad5667912ab3846b0b15b061d7c897890ca8917cdc14cf00ae751e
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.