Package: mpack-dev
Source: mpack
Version: 0.8.0
Architecture: amd64
Maintainer: Maho Nakata <maho@riken.jp>
Installed-Size: 122473
Depends: libc6 (>= 2.14), libgcc1 (>= 1:4.4.0), libstdc++6 (>= 4.4.0), libgomp1, libquadmath0, libgmp-dev, libmpfr-dev, libmpc-dev, libqd-dev
Conflicts: mpack-dev
Provides: mpack-dev
Filename: ./amd64/mpack-dev_0.8.0_amd64.deb
Size: 27887902
MD5sum: 4b225e35cd839f3451f595370bc3dd6d
SHA1: 91e0554a43020459be7b79a37ae19e2c7a62538b
SHA256: 26707b6ae08d4c7b211ae92d7d57a3408361ee8eb22130f02de1007b68572235
Section: devel
Priority: optional
Description: mpack - mpack development files
 The MPACK is a multiprecision linear algebra package based on BLAS and LAPACK.
 This package is rewritten in C++, and supports several high precision
 libraries like GMP, MPFR and QD etc so that users can choose for user's
 convenience. The MPACK is a free software (2-clause BSD style license with
 original license by LAPACK).

Package: mpack-dev
Source: mpack
Version: 0.8.0
Architecture: i386
Maintainer: Maho Nakata <maho@riken.jp>
Installed-Size: 103768
Depends: libc6 (>= 2.4), libgcc1 (>= 1:4.4.0), libstdc++6 (>= 4.4.0), libgomp1, libquadmath0, libgmp-dev, libmpfr-dev, libmpc-dev, libqd-dev
Conflicts: mpack-dev
Provides: mpack-dev
Filename: ./i386/mpack-dev_0.8.0_i386.deb
Size: 24805836
MD5sum: d21bf6bfcf4b33f7dd1c83114694316b
SHA1: 54db6ce5fc210e93255965dc3f23738b571ae5f5
SHA256: b08ecdfa64b275139056ddb81240b3774f3ab3f4de9c4344e8e3400c2216c7e0
Section: devel
Priority: optional
Description: mpack - mpack development files
 The MPACK is a multiprecision linear algebra package based on BLAS and LAPACK.
 This package is rewritten in C++, and supports several high precision
 libraries like GMP, MPFR and QD etc so that users can choose for user's
 convenience. The MPACK is a free software (2-clause BSD style license with
 original license by LAPACK).

Package: pourrna
Version: 1.2.0-1
Architecture: amd64
Maintainer: Gregor Entzian <entzian@tbi.univie.ac.at>
Installed-Size: 1837
Depends: libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), viennarna-dev (>= 2.4.11)
Conflicts: pourrna
Provides: pourrna
Filename: ./amd64/pourrna_1.2.0-1_amd64.deb
Size: 264686
MD5sum: 13c69814860a91ac5ec71edf82823d77
SHA1: 039e375664888d845a6e24218c74dc228c02aa62
SHA256: c833f3380333d828c0a6c6ad217d2e5fe91cc602200371f37d9a57a1e4ff1e36
Section: science
Priority: optional
Description: Compute local minima and respective transition rates of an RNA energy landscape.
 pourRNA takes an RNA sequence as input and explores the landscape topology
 locally. This means the flooding algorithm will be applied for each gradient
 basin. The partition function for the basin and also for the transitions to
 neighbored minima will be calculated during the flooding.
 In order to speed up the computation of the rate matrix, local filtering
 techniques can be applied. These filters prune non-relevant transitions
 directly after flooding a gradient basin. As a result, the transition rates
 for the filtered landscape topology can be calculated faster than with global
 approaches. The advantage increases with increasing size of the energy
 landscape.

Package: pourrna
Version: 1.2.0-1
Architecture: i386
Maintainer: Gregor Entzian <entzian@tbi.univie.ac.at>
Installed-Size: 1847
Depends: libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.9), viennarna-dev (>= 2.4.11)
Conflicts: pourrna
Provides: pourrna
Filename: ./i386/pourrna_1.2.0-1_i386.deb
Size: 264490
MD5sum: cafa87a44f43ff78d18efb70cbef0ce6
SHA1: edcb7b8061652981b7ae7ec6a6c4f337993a5674
SHA256: 0de3e2929630938228b6c4cb41cb66734e58c84d327f971ea0550fb93abe2e40
Section: science
Priority: optional
Description: Compute local minima and respective transition rates of an RNA energy landscape.
 pourRNA takes an RNA sequence as input and explores the landscape topology
 locally. This means the flooding algorithm will be applied for each gradient
 basin. The partition function for the basin and also for the transitions to
 neighbored minima will be calculated during the flooding.
 In order to speed up the computation of the rate matrix, local filtering
 techniques can be applied. These filters prune non-relevant transitions
 directly after flooding a gradient basin. As a result, the transition rates
 for the filtered landscape topology can be calculated faster than with global
 approaches. The advantage increases with increasing size of the energy
 landscape.