Signaling networks are complex and may contain up to several hundred proteins. Potential variations in a network originate from different model system (e.g., ...
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What is spectral decomposition of signal?
What is a spectral decomposition?
Signaling networks modeled as Petri nets are one class of such graphical modeling and representations. These networks encode how different protein in specific ...
From this perspective, hierarchical spectral methods are proposed and applied for inferring similarities and dissimilarities from an ensemble of graphs that ...
Hierarchical decomposition of one connected component of the composite graph using recursive spectral bisection.
Spectral Decomposition of Signaling Networks. 2006. Parvin, Bahram;; Ghosh, Nimu;; Heiser, Laura;; Knapp, M.;; Talcott, C.;; Laderoute, K.;; Gray, J.;; Spellman ...
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Dive into the research topics of 'Spectral decomposition of signaling networks'. Together they form a unique fingerprint. Sort by; Weight · Alphabetically ...
In this paper, we present a neural network ap- proximation of a non-linear spectral decomposition. We report up to four orders of magnitude (×10, 000) speedup ...
1) A spectral decomposition technique is developed to decompose the linear quadratic control problem for network-coupled dynamical subsystems into L + 1 de-.
A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in ...