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The identification of disease genes is an essential issue to decipher the mechanisms of complex diseases. Many existing methods combine machine learning algorithms and network information to predict disease genes and are based on the ‘guilt by association’ assumption, where disease genes are considered to be close to each other in a biomolecular network. Although these methods have gained many novel...
S-system models for biological systems are derived from the generalized mass action law and are typically a group of nonlinear differential equations. Estimation of parameters in these models from experimental measurements is thus a nonlinear problem. In principle, all algorithms for nonlinear optimization can be used to estimate parameters in molecular biological systems, for example, Gauss-Newton...
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