ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

PLoS Computational Biology

Volumn 10, Issue 7, 2014, Pages

  Hasenauer, Jan ^a,b   Hasenauer, Christine ^c   Hucho, Tim ^c,d   Theis, Fabian J ^a,b  

^a INSTITUTE OF EPIDEMIOLOGY   (Germany)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c MAX PLANCK INSTITUTE FOR MOLECULAR GENETICS   (Germany)

^d UNIVERSITY HOSPITAL OF COLOGNE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CELLS; CYTOLOGY; MIXTURES; NEURONS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

BACTERIAL POPULATION; CELL-TO-CELL VARIABILITY; EXPERIMENTAL CONDITIONS; FUNCTIONAL CELLS; MECHANISTICS; MIXTURE MODELING; MIXTURE-MODELLING; MULTICELLULAR ORGANISMS; ORDINARY DIFFERENTIAL EQUATION MODELS; STRUCTURE AND DYNAMICS;

ORDINARY DIFFERENTIAL EQUATIONS;

MITOGEN ACTIVATED PROTEIN KINASE 1; MITOGEN ACTIVATED PROTEIN KINASE 3; NERVE GROWTH FACTOR; MITOGEN ACTIVATED PROTEIN KINASE;

ANIMAL CELL; ARTICLE; CONSTRAINED MIXTURE MODEL; CONTROLLED STUDY; ENZYME PHOSPHORYLATION; INFLAMMATORY PAIN; INSTRUMENT VALIDATION; MALE; MATHEMATICAL MODEL; NEUROPATHIC PAIN; NONHUMAN; ORDINARY DIFFERENTIAL EQUATION MODEL; PREDICTION; RAT; RELIABILITY; SENSORY NERVE CELL; ANIMAL; BIOLOGICAL MODEL; METABOLISM; PHYSIOLOGY; SIGNAL TRANSDUCTION; SPRAGUE DAWLEY RAT;

ANIMALS; EXTRACELLULAR SIGNAL-REGULATED MAP KINASES; MALE; MAP KINASE SIGNALING SYSTEM; MODELS, NEUROLOGICAL; NERVE GROWTH FACTOR; RATS; RATS, SPRAGUE-DAWLEY; SENSORY RECEPTOR CELLS;

EID: 84905460441     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003686     Document Type: Article

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