Exact(3)
Unlike traditional un-weighted gene co-expression networks in which two genes (nodes) are either connected or disconnected, the weighted gene co-expression analysis assigns a connection weight to each gene pair using soft-thresholding and thus is robust to parameter selection.
In contrast to traditional un-weighted gene co-expression networks where two genes (nodes) are either connected or disconnected, the weighted gene co-expression network analysis assigns a connection weight to each gene pair using soft-thresholding and thus is robust to parameter selection.
Unlike traditional un-weighted gene co-expression networks in which two genes (nodes) are either connected or disconnected, the weighted gene co-expression network analysis assigns a connection weight to each gene pair using soft-thresholding and thus is robust to parameter selection.
Similar(56)
But in ANN approach, a learning procedure is adopted for network to update network architecture and connection weights to perform efficiently.
In the supervised learning mechanism, NN is given the teaching data base and on the basis of this, it adjusts connection weights to produce the desired output.
An important contribution of this research is that it is demonstrated that ANNs need not be used simply as black boxes and cause-effect information can be quantitatively extracted from network connection weights to assist in model development and experimental design.
On the other hand, genes with large connection weights to an endophenotype may be closer to the development of hypertension.
These are simulated setting the relevant connection weights to zero and leaving all other parameters of the model unaltered.
For the update of the connection weights to the read-out units, we used either batch regression or online learning methods.
(2007a) with an S3 VTU layer, by setting up a moderate number of view-tuned units, each one of which is set to have connection weights to all neurons in the C2 layer that reflect the firing rate of each C2 unit to one exemplar of a class.
The third term is the input from IO defined as follows:
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