Due to computational costs and network speeds, it is impractical to process and manipulate such big RNA-seq data files through typical web-based tools.
As datasets grow, however, interactivity becomes a burden and a source of errors, and it becomes impractical to process large datasets of hundreds of trees and/or very large trees without automation.
Not only those interactions are context-dependent and thus cannot be understood by keeping cells in an inappropriate milieu, like that provided by 2D-cultures, but also they follow nonlinear dynamics which make impractical modeling processes with more than two variables.
Physics-based machining models typically require significant computational resources and time which makes them impractical for quick process optimization calculations in an industrial shop-floor setting.
As pointed out by Oda et al, [10] although Cambou and Klibanov [12] reported the kinetic resolution of (R,S -citronellol via transesterification with hog liver carboxylesterase,S -citronellol the instability of the enzyme makes that process impractical.
This requirement renders the process impractical at an industrial scale because of costs, possible contamination of the resulting biodiesel with traces of the emulsifier, and losses associated with the amphipathic nature of the additive.
This can be time consuming, laborious, and impractical for long processes.
