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As they explained in September in the journal PLoS Computational Biology, the modified algorithm was more efficient than existing ecosystem-extinction models at identifying which species' extinction would cause the greatest number of other species in the food web also to go extinct.
The modified algorithm was implemented in MatLab, using Kriging-type surrogate model.
The modified algorithm was presented without proof in Mintseris and Eisen (2006).
Our modified algorithm was intended to produce a cohort that was representative of type 2 diabetes as far as possible.
After scaled log2 IP/Input) data was generated, the modified algorithm was applied to carry out the one-sided Kolmogorov-Smirnov test on several adjacent probes using sliding windows to predict enriched regions across the microarray.
This modified algorithm was then implemented in a mobile decision support system for basal bolus insulin dosing, the GlucoTab® system (Joanneum Research GmbH [Graz, Austria] and Medical University of Graz [Graz, Austria]), which was subsequently customized and tested in a clinical study with 30 patients.
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Therefore, the modified algorithm is convergent.
Then, the modified algorithm is convergent.
This modified algorithm is called MFPEG algorithm in this article.
In this article, this modified algorithm is referred to as linear-encoding PEG (LPEG) algorithm.
However, the computational load of the modified algorithm is lower than the conventional method.
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