Estimation of biochemical network parameter distributions in cell populations Export

@article{citeulike:4503232, abstract = {Populations of heterogeneous cells play an important role in many biologicalsystems. In this paper we consider systems where each cell can be modelled byan ordinary differential equation. To account for heterogeneity, parametervalues are different among individual cells, subject to a distribution functionwhich is part of the model specification.Experimental data for heterogeneous cell populations can be obtained fromflow cytometric fluorescence microscopy. We present a heuristic approach to usesuch data for estimation of the parameter distribution in the population. Theapproach is based on generating simulation data for samples in parameter space.By convex optimisation, a suitable probability density function for thesesamples is computed.To evaluate the proposed approach, we consider artificial data from a simplemodel of the tumor necrosis factor (TNF) signalling pathway. Its maincharacteristic is a bimodality in the TNF response: a certain percentage ofcells undergoes apoptosis upon stimulation, while the remaining part staysalive. We show how our modelling approach allows to identify the reasons thatunderly the differential response.}, archivePrefix = {arXiv}, author = {Waldherr, Steffen and Hasenauer, Jan and Allg\"{o}wer, Frank}, citeulike-article-id = {4503232}, citeulike-linkout-0 = {http://arxiv.org/abs/0905.1191}, citeulike-linkout-1 = {http://arxiv.org/pdf/0905.1191}, day = {8}, eprint = {0905.1191}, keywords = {biochemistry, distribution, mathematical\_model, method, network, parameter, statistical\_method, tnf}, month = {May}, posted-at = {2009-05-11 18:53:31}, priority = {2}, title = {Estimation of biochemical network parameter distributions in cell populations}, url = {http://arxiv.org/abs/0905.1191}, year = {2009} }

TY - JOUR ID - citeulike:4503232 L3 - citeulike-article-id:4503232 N2 - Populations of heterogeneous cells play an important role in many biologicalsystems. In this paper we consider systems where each cell can be modelled byan ordinary differential equation. To account for heterogeneity, parametervalues are different among individual cells, subject to a distribution functionwhich is part of the model specification.Experimental data for heterogeneous cell populations can be obtained fromflow cytometric fluorescence microscopy. We present a heuristic approach to usesuch data for estimation of the parameter distribution in the population. Theapproach is based on generating simulation data for samples in parameter space.By convex optimisation, a suitable probability density function for thesesamples is computed.To evaluate the proposed approach, we consider artificial data from a simplemodel of the tumor necrosis factor (TNF) signalling pathway. Its maincharacteristic is a bimodality in the TNF response: a certain percentage ofcells undergoes apoptosis upon stimulation, while the remaining part staysalive. We show how our modelling approach allows to identify the reasons thatunderly the differential response. TI - Estimation of biochemical network parameter distributions in cell populations KW - biochemistry KW - distribution KW - mathematical_model KW - method KW - network KW - parameter KW - statistical_method KW - tnf AU - Waldherr, Steffen AU - Hasenauer, Jan AU - Allgöwer, Frank PY - 2009/May/08/ UR - http://arxiv.org/abs/0905.1191 ER -