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A symbolic computation of the observer gain often yields very large expressions.
We present algorithms for efficient symbolic simplification of such large expressions.
(2013) [12], we employ VEST in the automation of the calculation of high-order Lagrangians for the single particle guiding center system in plasma physics, a computation which illustrates its ability to handle very large expressions.
In addition, utilizing properties of the Levi-Civita symbol, the program can derive types of multi-term vector identities that are not recognized by reduction, subsequently applying these to simplify large expressions.
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Predicting such interactions from large expression datasets by performing targeted knock-down/knock-out approaches is a challenging task.
This condition leads to an extremely large expression containing algebraic and trigonometric functions of the architecture, position and orientation variables.
The proposed division strategy is invariant to monotonic grayscale changes, and shows to be particularly useful when there are large expression variations on the faces.
In this data set, parent node mutations resulted in large expression changes in their direct targets.
Noticeably, this correlation is mainly due to genes with large expression differences between species.
However, large scale protein quantification remains challenging, in particular due to the large expression range and proteome complexity [19] [21].
However, the CORG-method may disregard member genes that have consistent, but not large, expression changes under different phenotypes.
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