Package: imp-dev
Architecture: amd64
Version: 2.10.1-1
Priority: optional
Section: libdevel
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 5376
Depends: imp (= 2.10.1-1), 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_2.10.1-1_amd64.deb
Size: 718544
MD5sum: 5245d8cdd4fa10728126a2de9321cf18
SHA1: d7104eacbca1f055551731402c01db258c456589
SHA256: a700714684fa70aa9ee1d5e8d1d51e29d5fea3c0ab65bc155fc53d9bfb80ad7d
SHA512: 4b3f5677fdf172f977382984330049bac8757e88cc7129014debe96dabe6ced2eb3eb7422bfd40221a8c35e7881b2409cf94e1b8cb1c69cdd98c529020a2b6cf
Homepage: https://integrativemodeling.org/
Description: The Integrative Modeling Platform
 Headers to compile against IMP.

Package: imp-python3
Architecture: amd64
Version: 2.10.1-1
Priority: optional
Section: libs
Source: imp
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 63938
Depends: imp (= 2.10.1-1), python3, python3-numpy, python3-protobuf
Filename: bionic/imp-python3_2.10.1-1_amd64.deb
Size: 8866776
MD5sum: 45f081f5c92a03fd20f5756a5e10f1a9
SHA1: 0968ddbe43d3919f1c8147d06a4653fedc8712e0
SHA256: d9c1cfaffba9ab79f995e9f29f17cf4e38da38a31cfa4ee7fc3857ab2fed8114
SHA512: 75e59657ed41674b71fa8b32b2407dcd44f871397856cfef67093ecb9aa0905ade07ab1aaf6de5ed0c0d28a4d4e80396e7bde6969483c51acdc5e2783fdbd13d
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: 2.10.1-1
Priority: optional
Section: libs
Maintainer: Ben Webb <ben@salilab.org>
Installed-Size: 413796
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_2.10.1-1_amd64.deb
Size: 46004716
MD5sum: be6d52ba42305f93419173ee95c5f390
SHA1: 260ca8062f873cfe23a57f07653e1be9f56bf63a
SHA256: a489abd0bbdc9f8945ae3fafdc86e31aa1162c9e751ee1184f56418b50b8da8e
SHA512: c5d21fffc73ad90cd7baeb1347fa2a04e3f30892bad96e3fe1d4de5490523b604024ab2fe7594dfc7ba301e0b42d9dcd1e897e16033dad58fcafc333765ff244
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.