Package: mpack-dev Source: mpack Version: 0.8.0 Architecture: amd64 Maintainer: Maho Nakata 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 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 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 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.