Inferring gene regulatory networks via nonlinear state-space models and exploiting sparsity

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 9, Issue 4, 2012, Pages 1203-1211

  Noor, Amina ^a   Serpedin, Erchin ^a   Nounou, Mohamed ^b   Nounou, Hazem ^b  

^a Department of Electrical and Computer Engineering   (United States)

^b TEXAS A AND M UNIVERSITY AT QATAR   (Qatar)

Author keywords

Gene regulatory network; Kalman filter; LASSO; parameter estimation; particle filter

Indexed keywords

BIOLOGICAL DATA; FILTER-BASED; GENE EXPRESSION TIME SERIES; GENE NETWORKS; GENE REGULATORY NETWORKS; LASSO; LEAST SQUARES REGRESSION; MICROARRAY DATA; NETWORK INFERENCE; NON-LINEARITY; NONLINEAR STATE SPACE MODELS; PARAMETER VECTORS; PARAMETERS CHARACTERIZING; PARTICLE FILTER; REALISTIC SCENARIO; REGULATORY NETWORK; STATE ESTIMATES; STATE ESTIMATION ALGORITHMS; STATE SPACE MODEL; SYNTHETIC DATA; UNSCENTED KALMAN FILTER;

APPROXIMATION ALGORITHMS; COMPUTER SIMULATION; GENE EXPRESSION; INFERENCE ENGINES; KALMAN FILTERS; MEAN SQUARE ERROR; NONLINEAR FILTERING; STATE ESTIMATION; STATE SPACE METHODS;

PARAMETER ESTIMATION;

ALGORITHM; ANIMAL; ARTICLE; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; DNA MICROARRAY; DROSOPHILA MELANOGASTER; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETIC DATABASE; METHODOLOGY; NONLINEAR SYSTEM;

ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, GENETIC; DROSOPHILA MELANOGASTER; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; MODELS, GENETIC; NONLINEAR DYNAMICS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 84861507910     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2012.32     Document Type: Article

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