The blind source separation (BSS) method proposed in 2001 by Belouchrani et al. (41) is a neural network based method that separates a linear mixture of stationary independent sources received by different sensors by the use of higher-order statistical moments in the learning algorithm.
Other clustering algorithms, such as a graph-theoretic approach [ 45], and a neural network based method SOM [ 46], as well as different parameter options, will be incorporated in future releases of the database.
In this paper, we introduce a Bayesian network based method to differentiate predictive and non-predictive connections in a transcriptional regulatory network given a body of gene expression data.
For solvent accessibility prediction, SPINE-X is a neural network based method, whereas SANN is based on nearest neighbor.
A novel neural network based method for modeling of rate-dependent hysteresis in piezoelectric actuators is proposed.
For instance, as illustrated in Figure 4D, NORSnet, predicts the protein to be entirely lacking unstructured loops and PROFsec, a profile neural network based method predicting secondary structure, predicts the disordered region to be mostly helical.
In the present work, we apply a miRNA regulatory network based method to identify novel microRNA biomarkers associated with the early diagnosis of sepsis.
In this design, ceramic sample classification is achieved with three well-known methods, a standard statistical learning method termed k-Nearest Neighbours (k-NN), a method using Decision Trees (C4.5) and a more complex neural network based method known as Learning Vector Quantisation (LVQ).
We developed an algorithm called NetPathID (NETwork based method for PATHway IDentification) to discover pathways disrupted by copy number alterations across cancers.
Thus, CPRBF network based method is effective to real-time fault detection.
