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However, it is difficult to automate phylogenetic analysis approaches for genome-wide analysis, therefore prediction of orthologs for large genome datasets has been typically performed using homology based methods which compare reciprocal-best-BLAST-hits (RBH).
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Further improvement in phylogeny estimation is to be expected if secondary structure information can be incorporated in Maximum Likelihood (ML) or Bayesian inference (BI) methods, because these character-based methods can be superior compared to distance based methods which discard character-state information.
Compared to previous protein feature based method, which focused on post-transcriptional level regulation, genomic feature based method demonstrates increased prediction performance.
To our knowledge, there is no known work based on CFD method which compares different phases of underwater front crawl hand motion with appropriate changes of hand orientation.
We based this analysis on an intention to treat method, which compares patients according to their assigned intervention or control group.
As a sequence-based method, the hybrid-property based method should be compared to other sequence-based method.
We found that the oligonucleotide based methods gave different results compared to that of the proteome based methods.
Its measured average porosity compares favorably to other porosity methods including two volumetric based methods and ASTM D7063 which uses a vacuum sealing device.
Both tables show that nanoparticle based methods hold many advantages as compared to existing methods.
Methods based on departure from Hardy Weinberg equilibrium are more powerful than those which compare cases to controls.
Compared to FFT based methods, the semi-Lagrangian methods provide a local approximation (which is important in the context of parallelization).
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