[Cdd-commits] r598 - in projects/med/trunk/debian-med: debian tasks

[CDD Subversion Commit]

Author: tille
Date: Wed Mar 12 20:40:18 2008
New Revision: 598

Modified:
   projects/med/trunk/debian-med/debian/changelog
   projects/med/trunk/debian-med/tasks/bio-dev
Log:
libGenome, libMeme (required for Mauve)


Modified: projects/med/trunk/debian-med/debian/changelog
==============================================================================
--- projects/med/trunk/debian-med/debian/changelog	(original)
+++ projects/med/trunk/debian-med/debian/changelog	Wed Mar 12 20:40:18 2008
@@ -1,4 +1,13 @@
-debian-med (0.17) unstable; urgency=low
+debian-med (0.18) unstable; urgency=low
+
+  * tasks/bio-dev
+    - Added libgenome
+    - Added libmems as prospective package
+
+ -- Andreas Tille <tille at debian.org>  Wed, 12 Mar 2008 21:38:09 +0100
+
+debi
+an-med (0.17) unstable; urgency=low
 
   * tasks/bio:
     - Added emboss-kaptain as prospective package

Modified: projects/med/trunk/debian-med/tasks/bio-dev
==============================================================================
--- projects/med/trunk/debian-med/tasks/bio-dev	(original)
+++ projects/med/trunk/debian-med/tasks/bio-dev	Wed Mar 12 20:40:18 2008
@@ -15,6 +15,8 @@
 
 Recommends: libqsearch
 
+Depends: libgenome-1.3-1
+
 Depends: bioclipse
 Homepage: http://www.bioclipse.net/
 Responsible: 
@@ -65,3 +67,19 @@
  features associated with DNA, RNA and Protein sequences.
  .
  This package provides a Perl module to use GFF objects.
+
+Depends: libmems-1.5-1
+Homepage: http://asap.ahabs.wisc.edu/software/software-development-libraries/libmems.html
+Responsible: Andreas Tille <tille at debian.org>
+License: GPL
+Pkg-URL: http://people.debian.org/~tille/packages/libmems/
+Pkg-Description: library to support DNA string matching and comparative genomics
+ libMems is a freely available software development library to support DNA
+ string matching and comparative genomics. Among other things, libMems
+ implements an algorithm to perform approximate multi-MUM and multi-MEM
+ identification. The algorithm uses spaced seed patterns in conjunction
+ with a seed-and-extend style hashing method to identify matches. The method
+ is efficient, requiring a maximum of only 16 bytes per base of the largest
+ input sequence, and this data can be stored externally (i.e. on disk) to
+ further reduce memory requirements.
+        
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