fsa 1.15.9+dfsg-3 source package in Ubuntu

Changelog

fsa (1.15.9+dfsg-3) unstable; urgency=medium

  * Team upload.
  * Add autopkgtests.
    Closes: #848328

 -- Sascha Steinbiss <email address hidden>  Fri, 16 Dec 2016 16:41:29 +0000

Upload details

Uploaded by:
Debian Med on 2016-12-16
Uploaded to:
Sid
Original maintainer:
Debian Med
Architectures:
any
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Zesty release on 2016-12-17 universe misc

Downloads

File Size SHA-256 Checksum
fsa_1.15.9+dfsg-3.dsc 1.9 KiB e636b6f608bdbd6ea35825eb1b36d8c5c2b99c6ce93162bea3cdb6da88c5a547
fsa_1.15.9+dfsg.orig.tar.xz 545.6 KiB c3a845122e08f5e3c0fb96ef5133270a386c4ac6198856fc56aa2a796c0a6377
fsa_1.15.9+dfsg-3.debian.tar.xz 12.7 KiB fcaeba866cd7c5c949117e96b5878f0d8da2ba93cefeea0e88de15462cdec2aa

Available diffs

No changes file available.

Binary packages built by this source

fsa: Fast Statistical Alignment of protein, RNA or DNA sequences

 FSA is a probabilistic multiple sequence alignment algorithm which uses
 a "distance-based" approach to aligning homologous protein, RNA or DNA
 sequences. Much as distance-based phylogenetic reconstruction methods
 like Neighbor-Joining build a phylogeny using only pairwise divergence
 estimates, FSA builds a multiple alignment using only pairwise
 estimations of homology. This is made possible by the sequence annealing
 technique for constructing a multiple alignment from pairwise
 comparisons, developed by Ariel Schwartz.
 .
 FSA brings the high accuracies previously available only for
 small-scale analyses of proteins or RNAs to large-scale problems such as
 aligning thousands of sequences or megabase-long sequences. FSA
 introduces several novel methods for constructing better alignments:
  * FSA uses machine-learning techniques to estimate gap and
    substitution parameters on the fly for each set of input sequences.
    This "query-specific learning" alignment method makes FSA very robust:
    it can produce superior alignments of sets of homologous sequences
    which are subject to very different evolutionary constraints.
  * FSA is capable of aligning hundreds or even thousands of sequences
    using a randomized inference algorithm to reduce the computational
    cost of multiple alignment. This randomized inference can be over ten
    times faster than a direct approach with little loss of accuracy.
  * FSA can quickly align very long sequences using the "anchor
    annealing" technique for resolving anchors and projecting them with
    transitive anchoring. It then stitches together the alignment between
    the anchors using the methods described above.
  * The included GUI, MAD (Multiple Alignment Display), can display the
    intermediate alignments produced by FSA, where each character is
    colored according to the probability that it is correctly aligned

fsa-dbgsym: debug symbols for package fsa

 FSA is a probabilistic multiple sequence alignment algorithm which uses
 a "distance-based" approach to aligning homologous protein, RNA or DNA
 sequences. Much as distance-based phylogenetic reconstruction methods
 like Neighbor-Joining build a phylogeny using only pairwise divergence
 estimates, FSA builds a multiple alignment using only pairwise
 estimations of homology. This is made possible by the sequence annealing
 technique for constructing a multiple alignment from pairwise
 comparisons, developed by Ariel Schwartz.
 .
 FSA brings the high accuracies previously available only for
 small-scale analyses of proteins or RNAs to large-scale problems such as
 aligning thousands of sequences or megabase-long sequences. FSA
 introduces several novel methods for constructing better alignments:
  * FSA uses machine-learning techniques to estimate gap and
    substitution parameters on the fly for each set of input sequences.
    This "query-specific learning" alignment method makes FSA very robust:
    it can produce superior alignments of sets of homologous sequences
    which are subject to very different evolutionary constraints.
  * FSA is capable of aligning hundreds or even thousands of sequences
    using a randomized inference algorithm to reduce the computational
    cost of multiple alignment. This randomized inference can be over ten
    times faster than a direct approach with little loss of accuracy.
  * FSA can quickly align very long sequences using the "anchor
    annealing" technique for resolving anchors and projecting them with
    transitive anchoring. It then stitches together the alignment between
    the anchors using the methods described above.
  * The included GUI, MAD (Multiple Alignment Display), can display the
    intermediate alignments produced by FSA, where each character is
    colored according to the probability that it is correctly aligned