  We study a method of seed-based lossless filtration for approximate string
matching and related bioinformatics applications. The method is based on a
simultaneous use of several spaced seeds rather than a single seed as studied
by Burkhardt and K\"arkk\"ainen [1]. We present algorithms to compute several
important parameters of seed families, study their combinatorial properties,
and describe several techniques to construct efficient families. We also report
a large-scale application of the proposed technique to the problem of
oligonucleotide selection for an EST sequence database.
