The phrase "alignment likelihood" is correct and usable in written English.
It can be used in contexts related to statistics, machine learning, or any field where the probability of alignment between variables or models is being discussed.
Example: "The alignment likelihood of the two datasets suggests a strong correlation between the variables."
Alternatives: "probability of alignment" or "likelihood of alignment".
Plans are also underway to introduce additional high performance computing technologies, e.g., distributed computing and cloud computing, in order to mitigate the computational load of sequence alignment, likelihood estimation and bootstrapping, which is heavy along with the large amount of input data.
For detailed description of the alignment likelihood estimation please refer to Glaus et al. (2012).
For the whole database alignment maximum likelihood trees were calculated using the MPI version of raxmlHPC [24] on a Linux cluster of 32 PCs containing 32 AMD Opteron cpus.
Following alignment, maximum likelihood phylogenetic trees for PMEs and PMEIs were constructed.
On our simulated protein families, this approach led to even better results than the classical approach based on multiple alignment and likelihood.
Using the nucleotide alignment, hierarchical likelihood ratio tests indicated that the Tamura 3-parameter + Γ (with a = 1.24) model was the most appropriate model of DNA sequence evolution.
According to the Akaike information criterion LG+F+G was optimal for phylogenetic analysis (see Additional file 9 and Additional file 10 for protein alignment and likelihood scores, respectively).
A similar phylogenetic analysis, restricted to N-terminal NBDs of T. urticae, was also performed (optimal model according to the Akaike Information Criterion: LG+I+G+F, see Additional file 9 and Additional file 10 for protein alignment and likelihood score, respectively).
LR ¯ – the per alignment mean likelihood ratio of a nuGTR + Param against the corresponding nuGTR; % ¯ (SE) – the per alignment mean (and standard error) relative importance of a parameter, expressed as a percentage of the diGTR LR; Rank ¯ (SE) – the per alignment mean (and standard error) rank of the LR.
Building upon this test, the exon data was used to generate MJ network because of the absence of recombination signal in alignment (Log Likelihood = -1911.85; AIC = 4061.69), while the exon + intron and intron data were not used to reconstructed MJ network due to potential recombination signal.
In summary, mycobacteriophage cluster relationships may be determined using either whole genomes in an alignment-free FFP analysis or predicted using single genes (such as TMP) in a global-alignment maximum likelihood analysis.
