Author: lkajan-guest
Date: 2012-07-11 12:09:05 +0000 (Wed, 11 Jul 2012)
New Revision: 11730

Modified:
   trunk/packages/norsnet/trunk/debian/control
Log:
added Deb Med Team as maintainer, Laszlo as uploader; added Vcs fields; add DM 
Upload field; streamlined description

Modified: trunk/packages/norsnet/trunk/debian/control
===================================================================
--- trunk/packages/norsnet/trunk/debian/control 2012-07-11 12:08:01 UTC (rev 
11729)
+++ trunk/packages/norsnet/trunk/debian/control 2012-07-11 12:09:05 UTC (rev 
11730)
@@ -1,22 +1,24 @@
 Source: norsnet
 Section: science
 Priority: extra
-Maintainer: Guy Yachdav <[email protected]>
-Uploaders: Christian Mertes <[email protected]>
+Maintainer: Debian Med Packaging Team 
<[email protected]>
+Uploaders: Christian Mertes <[email protected]>, Laszlo Kajan 
<[email protected]>
 Build-Depends: debhelper (>= 8)
 Standards-Version: 3.9.3
 Homepage: http://rostlab.org/
+Vcs-Svn: svn://svn.debian.org/debian-med/trunk/packages/norsnet/trunk/
+Vcs-Browser: 
http://svn.debian.org/wsvn/debian-med/trunk/packages/norsnet/trunk/
+DM-Upload-Allowed: yes
 
 Package: norsnet
 Architecture: all
 Depends: ${shlibs:Depends}, ${misc:Depends}, profnet-norsnet
 Recommends: pp-popularity-contest, profphd, profbval
-Description: identifies unstructured loops from sequence
- NORSnet was trained to distinguish between very long contiguous segments with
+Description: tool to identify unstructured loops from protein sequence or 
alignment
+ NORSnet can distinguish between very long contiguous segments with
  non-regular secondary structure (NORS regions) and well-folded proteins.
+ .
  NORSnet was trained on predicted information rather than on experimental data.
- Therefore, it was optimized on a large data, which is not biased by today's
- experimental means of capturing disorder. Thus, NORSnet reached into regions
- in sequence space that are not covered by the specialized disorder predictors.
- One disadvantage of this approach is that it is not optimal for the
- identification of the "average" disordered region.
+ This allows NORSnet to reach into regions in sequence space that are not 
covered
+ by specialized disorder predictors.  One disadvantage of this approach is 
that it
+ is not optimal for the identification of the "average" disordered region.


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