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Both approaches exploited the weights of a linear support vector regression model to extract patterns which are important for activity or selectivity against a certain protein target.
Most of the above approaches exploited so far to some degree are quite complicated and require sophisticated transceiver system and demodulation scheme.
The phenomenon of exon skipping was independent of the genome editing approaches exploited, Cas9 or ZFN.
The in vivo phage display technology was used to identify molecules selectively expressed on tumor endothelium [ 8, 9], while other approaches exploited the in vivo proteomic analysis to detect antigens accessible from the vasculature [ 10, 11].
Traditional approaches exploited genomic data and prioritized genes for a disease if the genes are functionally similar to the known disease genes (Aerts et al., 2006; Franke et al., 2006; Köhler et al., 2008; Xu and Li, 2006).
In this category some methods used a random walk or a heat kernel [19], while others applied Web and social networks methods on a protein protein interaction (PPI) network [20], and other approaches exploited PPI and pathway information to prioritize candidate genes [21,15].
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These approaches exploit the spatial local information for extracting structural information such as edges or textures.
Therefore, these approaches exploiting TDMA are not suitable for our target application.
In the latter case, several approaches exploit ANNs for the adaptation.
Integrated guidance and control (IGC) approaches exploit the synergy between guidance and control designs.
Both approaches exploit time frequency sparsity under full data and compressed observations.
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