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Pournara and Wernisch (2008) [ 6] extend the Bayesian factor analysis approach for reconstructing TFAs and connections by integrating correlation between time points.
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Non-probabilistic methods, developed in the field of robust optimization were shown to have advantages over classical stochastic methods in several aspects such as: tractability, non-necessity of full probabilistic information, and the ability to integrate correlation of uncertain variables without adding complexity.
Using all gene pairs we obtain the integrated correlation score, an overall measurement of agreement between the two studies.
We modelled the E. coli datasets by using the ensemble approach integrating both correlation and ratio procedures as described above.
We are interested in studying the relationship between gene expression patterns and projection target correlations by integrating those two correlation matrices.
GDL integrates the correlation structures among genetic markers and traits simultaneously.
In the current analysis, we integrate metabolite correlation data with publicly available gene-coexpression data to obtain insights on the relationship between metabolites and gene regulations.
Here, we inspired from RotBoost technique and suggest a two-stage ensemble learning methodology by integrating fast correlation-based filter feature selection and independent component analysis- (ICA-) based RotBoost ensemble classification.
In the present work, a new correlation-based clustering method, referred to as NC-spectral clustering, is proposed by integrating the nearest correlation (NC) method and spectral clustering.
In the present work, a new clustering method, referred to as NC-spectral clustering, is proposed by integrating the nearest correlation (NC) method and spectral clustering.
We first proposed an approach for computing the fading cross-correlation, i.e., it is approximated by integrating the cross-correlation coefficients of the small-scale fadings in the same delay bins of two channels.
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