Improved Multiple Sequence Alignments Using Coupled Pattern Mining

Assessing Multiple Sequence Alignments Using Visual Tools

Multiple Sequence Alignments in Linguistics

In this study we apply and evaluate an iterative pairwise alignment program for producing multiple sequence alignments, ALPHAMALIG (Alonso et al., 2004), using as material the phonetic transcriptions of words used in Bulgarian dialectological research. To evaluate the quality of the multiple alignment, we propose two new methods based on comparing each column in the obtained alignments with the...

Evolving Better Multiple Sequence Alignments

Aligning multiple DNA or protein sequences is a fundamental step in the analyses of phylogeny, homology and molecular structure. Heuristic algorithms are applied because optimal multiple sequence alignment is prohibitively expensive. Heuristic alignment algorithms represent a practical trade-off between speed and accuracy, but they can be improved. We present EVALYN (EVolved ALYNments), a novel...

KalignP: Improved multiple sequence alignments using position specific gap penalties in Kalign2

SUMMARY Kalign2 is one of the fastest and most accurate methods for multiple alignments. However, in contrast to other methods Kalign2 does not allow externally supplied position specific gap penalties. Here, we present a modification to Kalign2, KalignP, so that it accepts such penalties. Further, we show that KalignP using position specific gap penalties obtained from predicted secondary stru...

Using muscle to produce multiple sequence alignments in Bioconductor

Producing high-quality multiple sequence alignments of DNA, RNA, or amino acid sequences is often an essential component of any comparative sequence-based study. The MUSCLE algorithm employs a progressive alignment approach to optimise pairwise alignment scores, and achieves both high accuracy and reduced computational time even when handling thousands of sequences (Edgar, 2004,a). The R packag...