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Identifying Biological Network Structure, Predicting Network Behavior, and Classifying Network State With High Dimensional Model Representation (HDMR)

This work presents an adapted Random Sampling - High Dimensional Model Representation (RS-HDMR) algorithm for synergistically addressing three key problems in network biology: (1) identifying the structure of biological networks from multivariate data, (2) predicting network response under previously unsampled conditions, and (3) inferring experimental perturbations based on the ...

Analysis of gene network robustness based on saturated fixed point attractors

The analysis of gene network robustness to noise and mutation is important for fundamental and practical reasons. Robustness refers to the stability of the equilibrium expression state of a gene network to variations of the initial expression state and network topology. Numerical simulation of these variations is commonly used for the assessment of robustness. Since there exists a ...

High efficiency classification of children with autism spectrum disorder

. Biochemical and adaptive behavior data from ASD, NEU, and SIB participants. (CSV) Conceptualization: Genyuan Li, Herschel Rabitz. Data curation: Genyuan Li, Olivia Lee. Formal analysis: Genyuan Li, Olivia Lee ... , Herschel Rabitz. Funding acquisition: Genyuan Li, Herschel Rabitz. Investigation: Genyuan Li, Olivia Lee, Herschel Rabitz. Methodology: Genyuan Li, Herschel Rabitz. Project administration: Herschel