To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis.
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Growth curve analysis of sedentary plant parasitic nematodes on different hosts and at different population densities is used to assess plant suitability including their resistance and tolerance. The estimated parameters of host suitability can be used in pest management programs for economic important species such as potato cyst nematodes.
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