Source: hmmer Maintainer: Debian Med Packaging Team Uploaders: Andreas Tille Section: science Priority: optional Build-Depends: debhelper-compat (= 13), libdivsufsort-dev, python3 Standards-Version: 4.6.2 Vcs-Browser: https://salsa.debian.org/med-team/hmmer Vcs-Git: https://salsa.debian.org/med-team/hmmer.git Homepage: http://hmmer.org/ Rules-Requires-Root: no Package: hmmer Architecture: any-amd64 any-i386 arm64 powerpc ppc64 x32 Depends: ${shlibs:Depends}, ${misc:Depends} Suggests: hmmer-doc (>= ${source:Version}) Description: profile hidden Markov models for protein sequence analysis HMMER is an implementation of profile hidden Markov model methods for sensitive searches of biological sequence databases using multiple sequence alignments as queries. . Given a multiple sequence alignment as input, HMMER builds a statistical model called a "hidden Markov model" which can then be used as a query into a sequence database to find (and/or align) additional homologues of the sequence family. Package: hmmer-doc Architecture: all Multi-Arch: foreign Section: doc Depends: ${misc:Depends} Recommends: hmmer (>= ${source:Version}), evince | pdf-viewer Description: profile hidden Markov models for protein sequence analysis (docs) HMMER is an implementation of profile hidden Markov model methods for sensitive searches of biological sequence databases using multiple sequence alignments as queries. . Given a multiple sequence alignment as input, HMMER builds a statistical model called a "hidden Markov model" which can then be used as a query into a sequence database to find (and/or align) additional homologues of the sequence family. . This package contains the documentation and a tutorial for the hmmer package. Package: hmmer-examples Architecture: any Section: doc Depends: ${misc:Depends}, libperl4-corelibs-perl Multi-Arch: foreign Description: profile hidden Markov models for protein sequence analysis (examples) HMMER is an implementation of profile hidden Markov model methods for sensitive searches of biological sequence databases using multiple sequence alignments as queries. . Given a multiple sequence alignment as input, HMMER builds a statistical model called a "hidden Markov model" which can then be used as a query into a sequence database to find (and/or align) additional homologues of the sequence family. . This package contains example files to test the hmmer package.