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Once the association parameters for all proteins in the candidate PPIN were identified for each protein, significant protein associations were determined using the interaction model order detection method based on estimated association abilities, that is, to detect the interaction number M i in (2).
To remove false positive PPIs from each candidate PPIN for different biological conditions, we used both a PPI model and a model order detection method to prune each candidate PPIN using the corresponding microarray data to approach the actual PPIN.
Once the association parameters for all proteins in the candidate PPI network were identified for each protein, the significant protein associations were determined using the interaction model order detection method based on the estimated association abilities.
Finally, we prune away the insignificant regulatory genes by AIC model order detection method in system identification [ 22] to refine the gene regulatory network of inflammatory response to bacterial endotoxin.
The AIC system order detection method (Additional file 2) was employed to prune false-positive PPIs to obtain real PPI networks of normal and cancer cells: in other words, we used the reverse engineering method to construct the PPI networks of normal and cancer cells.
After organizing the cancer microarray data and PPI data, we used a PPI model, the maximum likelihood parameter estimation method and a model order detection method together to prune each candidate PPIN by the corresponding microarray data to approach the actual PPIN of each cancer.
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A technique based on a high-resolution analysis algorithm and an order-detection method is presented here, with the aim of filling the gap between the low- and the high-frequency domains (30%<μ<100%).
2) In data without a natural order, an appropriate outlier detection method should be selected instead of using XmR - some simple examples being a) Tukey's method of "fences" b) the 3 sigma rule (note this corresponds to using an average and standard deviation chart).
Second, we approximate the reference contour using a Gaussian mixture model (GMM) continuous optimization algorithm followed by an order-preserved foot-point detection method used to extract the feature points that correspond to the feature points of the floating contours.
The mail order industry needs something clever detection method.
Firstly, we improve obstacle detection method in order to decrease the detection miss by using plane segmentation on organized point cloud and eliminating the assumption that obstacles are on the ground.
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Justyna Jupowicz-Kozak
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