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The proposed technique is an enhancement and improvement to the method proposed in [32].
Although correlation has weak interpretative power, compared with discretization, it offers a powerful improvement to the method and carries the benefit of well-understood probability inference.
A possible improvement to the method described here could be to use a variable heterozygosity rate based on a moving average from the reference data set, but this has not been investigated further.
Likewise, addition of a secretion signal like honeybee "melittin" has been attempted in several occasions but did not yield any particular improvement to the method [ 102].
Whilst initial methods were developed to take this into consideration, we found that this provided no improvement to the method, yet yielded a significant speed decrease.
Finally, the third relevant improvement to the method comes from the inclusion of sequence profiles in place of the single protein sequence as input to the DFT of Atchley's functions.
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Including a relevance index (e.g. times cited; journal's impact factor) to balance the contribution of each publication is a possible improvement to the methods used here.
In the course of the experiment, we tested new code generation ideas, and developed several significant improvements to the method.
The results of these case studies have led to improvements to the method and suggestions for further research.
We present several generalizations to the existing results and improvements to the method based on Mawhin's coincidence degree theory.
He has then made several important improvements to the method and has been crucial to the dissemination of the ideas behind the decomposition of an observed time series into components with clear and interpretable statistical properties.
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