The Maximum Weight Trace Problem in Multiple Sequence Alignment
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
Bouma2: a high-performance input-aware multiple string-match algorithm
CIAA'11 Proceedings of the 16th international conference on Implementation and application of automata
A polynomial time solvable formulation of multiple sequence alignment
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
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Protein sequence alignments are more reliable the shorter the evolutionary distance. Here, we align distantly related proteins using many closely spaced intermediate sequences as stepping stones. Such transitive alignments can be generated between any two proteins in a connected set, whether they are direct or indirect sequence neighbours in the underlying library of pairwise alignments. We have implemented a greedy algorithm, MaxFlow, using a novel consistency score to estimate the relative likelihood of alternative paths of transitive alignment. In contrast to traditional profile models of amino acid preferences, MaxFlow models the probability that two positions are structurally equivalent and retains high information content across large distances in sequence space. Thus, MaxFlow is able to identify sparse and narrow active-site sequence signatures which are embedded in high-entropy sequence segments in the structure-based multiple alignment of large diverse enzyme superfamilies. In a challenging benchmark, MaxFlow yields better reliability and double coverage compared to available sequence alignment software. This promises to increase information returns from functional and structural genomics, where reliable sequence alignment is a bottleneck to transferring the functional or structural characterization of model proteins to entire protein families and superfamilies.