Alignment of the 12 protein coding genes was done by eye whereas the 22 tRNA genes and 12S+16S rRNA genes were aligned with a probabilistic multiple alignment approach using ProAlign Ver. 0.5 [ 57].
In the light of these findings, alignment-free distance-based reconstruction methods deserve special attention, as they circumvent potential pitfalls of the multiple alignment approach, especially with respect to divergent sequences, and can be advantageous in speed possibly without sacrificing reconstruction accuracy.
Once the homologues in different families had been identified, we built super-families, using a progressive multiple alignment approach.
As expected, the multiple-alignment approaches Clustal W and Clustal Ω (Sievers et al., 2011) were far slower than the alignment-free methods; the difference in speed between alignment-based and alignment-free methods was between three and four orders of magnitude.
However, the nearest-neighbor approach might be substantially biased toward one end in the phylogeny and does not take sequence conservation into account, whereas the multiple-alignment approach usually does not consider the exact phylogenetic position of the target species and a careful selection of the seed sequences is an additional parameter.
If they are defined, then the system could be modeled as a complex network, and multiple network alignment approaches [ 3, 4] that look for subgraphs that co-occur across multiple network instances for the same system's phenotype are putative candidates for the target component interplays.
More traditional approaches for associating functional informations to proteins such as used by the PROSITE [9], PRINTS [10] and Blocks [11] databases extract sequence motifs using multiple sequence alignment approaches in order to infer information on key functional residues.
Duplicons within this complex mosaic cannot be readily uncovered by conventional multiple sequence alignment approaches.
Multiple sequence alignment approaches to phylogenetic footprinting can be performed for a dramatically higher portion of genes (a 66% increase observed in this study) and lead to improved alignment quality (Kumar and Filipski 2007).
Based on SPARSE, we furthermore develop a fast multiple RNA alignment approach.
