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But once the particle size is set what are the next formulation parameters to highlight as critical?
In the next formulation, for a positive number a, [ a ] denotes the entire part of a (maximal integer which does not exceed a), and for natural a and b, we denote { a / b } = { r, r ≠ 0 b, r = 0, where r is residual from dividing a by b (and r = a if a < b ).
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Instead of solving (13) let us consider the next equivalent formulation: min p r ^ - A p 2 2 + τ p 1 subject to τ ≥ 0, p i ≥ 0 i = 1, …, G (14).
It is evident that the accuracy for these models (around 0.3 for toploc and 0.4 for Markov) is dramatically lower than in the next-cell formulation, indicating that this problem formulation is a more challenging task.
Figure 1 shows how the maximum predictability for the places formulation is peaked at 0.68, significantly lower than what we observe in the next-cell formulation.
(B) Accuracy for the Markov model in the next-place formulation.
Algorithm 1 Toploc prediction algorithm Figure 2 Accuracy of the prediction in the next-cell formulation.
Figure 5 (A) Accuracy for the toploc model in the next-place formulation.
Figure 3 Effect of spatial granularity of the accuracy for the Markov model in the next-cell formulation.
Figure 4 Effect of temporal sampling of the accuracy for the Markov model in the next-cell formulation.
We investigated their expression profiles and moved on to the next step, the formulation of a hypothesis of AS, i.e. definition of the exons involved and the mode of AS (e.g. cassette exon).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com