We selected RED, as this clustering-free approach has both recently been applied to P. falciparum and shown to detect motifs that clustering based approaches did not.
Sequence based approaches do not require prior knowledge of the transcriptome and are therefore useful for discovery and annotation of novel transcripts as well as for analysis of poorly annotated genomes.
Compared with the NURBS method, this neural network based approach does not need the derivation of complex equation provided that a limited number of offset points are obtained, and its accuracy can meet general engineering needs.
In contrast, our end-sequence based approach does not rely on a priori knowledge of the cpDNA sequence.
As a screen of parameter values becomes necessary in such a scenario, the Monte-carlo based approach doesn't prove to be efficient, as it generally takes longer time to numerically simulate the process and satisfy the imposed conditions.
Conversely, the wear factor based approach did not predict such differences.
While a threshold of approximately 2% was originally suggested for congeneric species in most invertebrate taxa [ 18], the success of threshold-based approaches does not rely upon finding a single universal threshold as different values could be applied to different higher taxa, depending upon their rates of speciation and molecular evolution.
Testing coevolution between sites is an essential complement to molecular-selection analysis, since methods designed to detect adaptive evolution based on Bayesian approaches do not account for evolutionary interdependence between protein residues, which would providing more biologically realistic results.
However, the base excess approach does not address the second problem associated with using the Henderson-Hasselbach equation alone (ie it still does not tell us about the mechanisms of metabolic acid base balance).
Studies solely based on top-down approaches do not adequately account for the heterogeneity of shale gas deposits and hence, are unlikely to appropriately capture the extraction costs of shale gas.
In addition, we are considering resources in addition to MEDLINE citations and full text documents, for which current methods based on machine learning approaches do not need to perform as expected.
