J. Comput. Biol. - Phylogeny construction with rigid gapped motifs.

Tópicos

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{ age(1611) year(1155) adult(843) }
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{ gene(2352) biolog(1181) express(1162) }
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{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
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Resumo

Patterns with gaps have traditionally been used as signatures of protein families or as features in binary classification. Current alignment-free algorithms construct phylogenies by comparing the repertoire and frequency of ungapped blocks in genomes and proteomes. In this article, we measure the quality of phylogenies reconstructed by comparing suitably defined sets of gapped motifs that occur in mitochondrial proteomes. We study the dependence between the quality of reconstructed phylogenies and the density, number of solid characters, and statistical significance of gapped motifs. We consider maximal motifs, as well as some of their compact generators. The average performance of suitably defined sets of gapped motifs is comparable to that of popular string-based alignment-free methods. Extremely long and sparse motifs produce phylogenies of the same or better quality than those produced by short and dense motifs. The best phylogenies are produced by motifs with 3 or 4 solid characters, while increasing the number of solid characters degrades phylogenies. Discarding motifs with low statistical significance degrades performance as well. In maximal motifs, moving from the smallest basis to bases with higher redundancy leads to better phylogenies.

Resumo Limpo

pattern gap tradit use signatur protein famili featur binari classif current alignmentfre algorithm construct phylogeni compar repertoir frequenc ungap block genom proteom articl measur qualiti phylogeni reconstruct compar suitabl defin set gap motif occur mitochondri proteom studi depend qualiti reconstruct phylogeni densiti number solid charact statist signific gap motif consid maxim motif well compact generat averag perform suitabl defin set gap motif compar popular stringbas alignmentfre method extrem long spars motif produc phylogeni better qualiti produc short dens motif best phylogeni produc motif solid charact increas number solid charact degrad phylogeni discard motif low statist signific degrad perform well maxim motif move smallest basi base higher redund lead better phylogeni

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