For this, we design a new version of the suffix array of alignment by using an alignment transformation and a new definition of the alignment-suffix.
We computationally test this hypothesis in comparative analyses of 16S and 23S rRNA sequence alignments by using a tensor decomposition, i.e., a framework for modeling composite data.
These candidates are predicted from sequence and structure-based alignments, by using a combination of thermodynamic and evolutionary constraints (such as compensating base pair changes) (Pedersen et al., 2006; Torarinsson et al., 2006, 2008; Washietl et al., 2005; Weinberg et al., 2007).
On the basis of maximum identity score, the sequences were selected and aligned by using a multiple alignment software program such as Clustal W. Distance matrix was generated using RDP database and the phylogenetic tree was constructed using MEGA 5 (Tamura et al. 2013).
To investigate sequence similarities between L. santarosai serovar Shermani strain LT821 and strain CCF, we examined the conservation of genes in an isolate of L. santarosai serovar Shermani genome and a sequence alignment analysis by using a VectorNTI tool.
Genes which could not be assigned using orthology information were further searched using BLASTP and tBLASTn alignments by using an e-value cut-off of e−.
We computationally test this hypothesis in comparative analyses of 16S and 23S rRNA sequence alignments [14] by using a tensor decomposition, i.e., a mathematical framework for modeling composite data with multiple types of degrees of freedom.
To verify the significance of the results, we performed the same analysis with the 10 simulated alignments obtained by using a posterior predictive approach for the mtp336 dataset, as described above.
To check for recombination events within the RVFV alignment, the alignment was examined by using a set of 6 detection methods implemented in RDP3 (20 ).
This alignment was modelled by using a combination of density functional theory (DFT) and molecular dynamics (MD) computational approaches that do not require the input of experimental data.
