SKINK: a web server for string kernel based kink prediction in α-helices

نویسندگان

  • Tim Seifert
  • Andreas Lund
  • Benny Kneissl
  • Sabine C. Mueller
  • Christofer S. Tautermann
  • Andreas Hildebrandt
چکیده

MOTIVATION The reasons for distortions from optimal α-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. Here, we present a new web server, called SKINK, for string kernel based kink prediction. Extending our previous study, we also annotate the most probable kink position in a given α-helix sequence. AVAILABILITY AND IMPLEMENTATION The SKINK web server is freely accessible at http://biows-inf.zdv.uni-mainz.de/skink. Moreover, SKINK is a module of the BALL software, also freely available at www.ballview.org.

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عنوان ژورنال:
  • Bioinformatics

دوره 30 12  شماره 

صفحات  -

تاریخ انتشار 2014