Package: imp-dev
Architecture: amd64
Version: 2.11.1-1
Priority: optional
Section: libdevel
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 5383
Depends: imp (= 2.11.1-1), 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_2.11.1-1_amd64.deb
Size: 719604
MD5sum: 58b05f98d522bcdd89045ed124bccd70
SHA1: 9a74dd96aff6ed4ed6565b09ce6244dc1cab7ecd
SHA256: 15aa1475fac19cff43939705a0ef129aa8e755c729b25277ec922e4a87025062
SHA512: 737fdeb65075171b5c46f10705513898b1b109848df2f43fa2036d990574c188742c2d5feb02f2aa8205c09bb4c5aa3c8290120bc0ba6188ecb53b596fc3ddac
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Headers to compile against IMP.

Package: imp-python3
Architecture: amd64
Version: 2.11.1-1
Priority: optional
Section: libs
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 63945
Depends: imp (= 2.11.1-1), python3, python3-numpy, python3-protobuf
Filename: bionic/imp-python3_2.11.1-1_amd64.deb
Size: 8864840
MD5sum: 165ab18ce89e1088fed242eea1c78b1c
SHA1: b99e9c099d6ae3f0c57a3352699739b93de4bae4
SHA256: 2483bf48b238e7e1df621005b11a9a1adfc702b4192a46fc7c12afd5f6b8b828
SHA512: 9685b170f9c00fcdbd076824dcf7760ce0000cc1c12fb73cb504bd22a405a21906946c79f5e8bb78c53f0126414b32ec56faa72a88e7cc6af2a582314778adf5
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: 2.11.1-1
Priority: optional
Section: libs
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 414516
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_2.11.1-1_amd64.deb
Size: 46083724
MD5sum: 3c6669ce50de75853284776b6eb0dd07
SHA1: 0430fe5a33527aa97c0ba68cb34484f751d5ab12
SHA256: 521c43534b54bbb9ceab01acbc8ba3f327760829f196ccdde049d00ce6f8c160
SHA512: c387d1400ef73734179e3243225d38e7383cbc6fdbf67730adad7a03af62f35fb40b42f6b1c58fe15acf9239aff1290dfc3c99fad146fa2832a13e876595e0f0
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.