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Game theory provides a formal framework for modeling such interactions.
A probabilistic framework is the most appropriate for modeling such interactions.
Moore and Ritchie describe the need for designing new computational methods for detecting high-order non-linear interactions since traditional approaches such as logistic regression have limited power when modeling such interactions in high-dimensional data [ 41, 42].
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There is also the potential for overfitting because of interactions between the physiological variables, but we did not have sufficient data to be able to model such interactions.
We believe a more expressive model that is able to model such interactions between coverage terms would improve on the current results.
Also, the molecule (in addition to the protein) undergoes conformational changes, underscoring the difficulty of computational methods to model such interactions.
To our knowledge, this is the first report to model such interactions with the allosteric site, providing new insights into the dissociation of HDAC3/SMRT complexes in colon cancer cells.
We use random-neighbour interaction rule to model such interaction among agents dependent on spatial location; wherein each agent randomly moves to a cell site with equal probability (Liu and Wang 2013; Gündüç 2015).
Due to the complex nature of the interaction between a tire and off-road environment, one usually needs to make simplifying assumptions when modeling such an interaction.
In this paper, we propose a general framework as a conceptual tool for modeling such an interaction, once specific technologies are selected and employed.
In our model such interactions were not implemented and thus boundary detection is not possible.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com