Space-efficient K-MER algorithm for generalized suffix tree
arXiv preprint arXiv:1703.02224, 2017•arxiv.org
Suffix trees have emerged to be very fast for pattern searching yielding O (m) time, where m
is the pattern size. Unfortunately their high memory requirements make it impractical to work
with huge amounts of data. We present a memory efficient algorithm of a generalized suffix
tree which reduces the space size by a factor of 10 when the size of the pattern is known
beforehand. Experiments on the chromosomes and Pizza&Chili corpus show significant
advantages of our algorithm over standard linear time suffix tree construction in terms of …
is the pattern size. Unfortunately their high memory requirements make it impractical to work
with huge amounts of data. We present a memory efficient algorithm of a generalized suffix
tree which reduces the space size by a factor of 10 when the size of the pattern is known
beforehand. Experiments on the chromosomes and Pizza&Chili corpus show significant
advantages of our algorithm over standard linear time suffix tree construction in terms of …
Suffix trees have emerged to be very fast for pattern searching yielding O (m) time, where m is the pattern size. Unfortunately their high memory requirements make it impractical to work with huge amounts of data. We present a memory efficient algorithm of a generalized suffix tree which reduces the space size by a factor of 10 when the size of the pattern is known beforehand. Experiments on the chromosomes and Pizza&Chili corpus show significant advantages of our algorithm over standard linear time suffix tree construction in terms of memory usage for pattern searching.
arxiv.org
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