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- W1613198911 abstract "Optimal sequence alignments depend heavily on alignment scoring parameters. Given input sequences, {em parametric alignment} is the well-studied problem that asks for all possible optimal alignment summaries as parameters vary, as well as the {em optimality region} of alignment scoring parameters which yield each optimal alignment. But biologically correct alignments might be {em suboptimal} for all parameter choices. Thus we extend parametric alignment to {em parametric $k$-best alignment}, which asks for all possible $k$-tuples of $k$-best alignment summaries $(s_1, s_2, ..., s_k)$, as well as the {em $k$-best optimality region} of scoring parameters which make $s_1, s_2, ..., s_k$ the top $k$ summaries. By exploiting the integer-structure of alignment summaries, we show that, astonishingly, the complexity of parametric $k$-best alignment is only polynomial in $k$. Thus parametric $k$-best alignment is tractable, and can be applied at the whole-genome scale like parametric alignment." @default.
- W1613198911 created "2016-06-24" @default.
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- W1613198911 date "2008-09-09" @default.
- W1613198911 modified "2023-09-27" @default.
- W1613198911 title "Parametric k-best alignment" @default.
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