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We selected SynTReN rather than GeneNetWeaver (the simulator used in DREAM3 and DREAM4) because the former is computationally more efficient and allowed us to vary independently the numbers of samples and network nodes.
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The effects on inferred network accuracy that stem from incorporating SNPs are independent of MCMC sampler, sample size, and network topology.
Use of household or venue-based probability sampling will improve sample and network diversity and better support population-level inference.
For a continuous-time linear system with constant reference input, the network-based proportional-integral (PI) control is developed to solve the output tracking control problem by taking time-varying sampling and network-induced delays into account.
We also calculate the classification time of different methods based on the nearest-neighbor classifier with Euclidean distance: FLBP with 0.007079 s per sample, NRLBPs with 0.005682 s per sample, and networks with 0.005043 s per sample.
This was facilitated by personnel training provided by the EBB organization, and by exchange of solutions within the network, including sharing rules for sample distribution and network acknowledgement in publications making use of EBB-supplied samples.
Therefore, we propose pre-clustering of input expression samples to approximate condition-specific grouping of samples and individual network construction of each group as a means for dynamic significance thresholding.
Original H2 permeation measurements were performed changing sample temperature and network structure and compared with CO2 and N2 transport data.
Given the sample size and network size, GC-VAR and DBN cannot be applied to this dataset.
The user interface also allows the user to load sample data and network for analysis.
Link-tracing designs such as snowball sampling, random walk methods, and network sampling are described, along with adaptive allocation and adaptive cluster sampling.
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