@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.
}
}