Package: mpack-dev Source: mpack Version: 0.8.0 Architecture: i386 Maintainer: Maho Nakata Installed-Size: 99902 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: 24813792 MD5sum: c58588eb2eca5aac229e76ae398ee854 SHA1: 79c36c0334fd2931a6b7ac61618adaf9c606439c SHA256: f139783b1833dd8dd720082cf875a64a665fbc1e97330ef7507e874253457a67 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: amd64 Maintainer: Maho Nakata Installed-Size: 121079 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: 26680886 MD5sum: 4526b8ce6d868ed8716cdbf30ae7108e SHA1: e873544eceb0368feca40a79d25d81b8008ecab2 SHA256: 0f38655ea7ed18ac33af9de68ebf33d21373a0c1be6c95e4051b545ee199ef8f 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: 1.1.0-1 Architecture: i386 Maintainer: Gregor Entzian Installed-Size: 3867 Depends: libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.8.1), viennarna-dev (>= 2.4.11) Conflicts: pourrna Provides: pourrna Filename: ./i386/pourrna_1.1.0-1_i386.deb Size: 392872 MD5sum: c0fa9ab4e5138f7db49def6d81f5b455 SHA1: beb0fb809327d8b3e4ef8885bbd8624c9740b721 SHA256: f527cc33543286a07984b5f4c6d02745c7742f4462888656f9596a0724fdb05e 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: 1.1.0-1 Architecture: amd64 Maintainer: Gregor Entzian Installed-Size: 3853 Depends: libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.8.1), viennarna-dev (>= 2.4.11) Conflicts: pourrna Provides: pourrna Filename: ./amd64/pourrna_1.1.0-1_amd64.deb Size: 407420 MD5sum: 555896177ba0e1333f5abf81a978220b SHA1: 83f41fa1a3a5725e5f1345f1b323c48b478750e8 SHA256: e7216da73f690be7f2cfeddae973d1d40d46fec0e9c7720ba537205281036080 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: 3867 Depends: libc6 (>= 2.8), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.8.1), viennarna-dev (>= 2.4.11) Conflicts: pourrna Provides: pourrna Filename: ./i386/pourrna_1.2.0-1_i386.deb Size: 393010 MD5sum: 52ba6a3a4797e2f6b7658bb63f7666bf SHA1: 589f7c6ccbeb550354c9a690f581d4a6a290d520 SHA256: f673f44faae6c92a8f0bb554def8931fde84c4671bb7ea12f42daf44b70a7367 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: amd64 Maintainer: Gregor Entzian Installed-Size: 3853 Depends: libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libstdc++6 (>= 4.8.1), viennarna-dev (>= 2.4.11) Conflicts: pourrna Provides: pourrna Filename: ./amd64/pourrna_1.2.0-1_amd64.deb Size: 408738 MD5sum: 0426d5da52a38507bd8f7dc95c7a793d SHA1: 31149aa2c06adea4b8854889b0c07ff745f46c95 SHA256: 6fa454adad0f5f0449f43b2bfbeab8d423b44ed0299ef2f75c6c8aaf2573427e 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.