@techreport{ZiePhiSon07,
  author =   {Alexander Zien and Petra Philips and S\"oren Sonnenburg},
  title =    {{Computing Positional Oligomer Importance Matrices (POIMs)}},
  month = {December},
  year =     {2007},
  institution =  {Fraunhofer Institute FIRST},
  type = {Research Report; Electronic Publication},
  number = {2},
  pdf =  {http://publica.fraunhofer.de/eprints/N-66645.pdf},
  abstract = {
	  We show how to efficiently compute Positional Oligomer Importance
	  Matrices (POIMs) which are a novel and powerful way to extract,
	  rank, and visualize higher order (i.e. oligo-nucleotide)
	  compositional information for nucleotide sequences. Given a scoring
	  function for nucleotide sequences which is linear
	  w.r.t. positionwise occurrences of oligomers, POIMs quantify the
	  increase (or decrease) of the expected score caused by information
	  about each k-mer at each position.  We demonstrate how to obtain a
	  recursive algorithm which enables us to efficiently compute POIMs by
	  using string index data structures.  This is especially useful for
	  scoring functions whose linear weighting is sparse, as is the case
	  for the scoring function produced by string kernel classifiers.
  }
}