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For OEW, a novel optimization model has been developed to accurately predict the interaction of droplets, semiconductor layers, and a programmable DLP-based optical source.
Since RNA-RNA interactions can be modeled computationally, several excellent programs have been developed to predict the interaction of miRNAs with target transcripts.
An analytical model is proposed to predict the interaction of two defects in lattice materials based on a single defect model.
With these feature vectors as input, standard machine learning methods such as Support Vector Machines (SVM), Naïve Bayes (NB) or Neural Networks (NN) can be used to predict the interaction of new drug target pairs.
Based on the observation of experiment (Leonard et al. 2014), composite damage like splitting might promote deflection, even crack of their neighboured aluminium, and therefore the cohesive zone element discussed in section 3 of this paper could help to predict the interaction of damages between composite and metal layer in FMLs for improved accuracy.
It is important to correctly and efficiently predict the interaction of substrate-enzyme and to predict their product in metabolic pathway.
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Molecular docking of E. coli Biotin Carboxylase (EcBC) enzyme was also performed in order to predict the interactions of the synthesized compounds.
Various empirical approaches have been developed to predict the interactions of coiled-coil proteins [25].
No one can predict the interactions of several million lines of code in one application combined with several million lines of code in another.
In a chaotic system you can look at the initial starting conditions and the topology of a simulation and try to predict the interactions of strange attractors as much as you like, but you generally don't really get what the hell the simulation is doing until you observe it in motion.
Node degree is a central property of gene networks [52] and in fact can be used to help predict the interactions of genes[53].
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