Analysis of Single-Cell Data: ODE Constrained Mixture by Carolin Loos

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By Carolin Loos

Carolin bogs introduces novel ways for the research of single-cell info. either ways can be utilized to check mobile heterogeneity and as a result increase a holistic figuring out of organic methods. the 1st procedure, ODE limited combination modeling, allows the id of subpopulation constructions and assets of variability in single-cell photo info. the second one procedure estimates parameters of single-cell time-lapse info utilizing approximate Bayesian computation and is ready to make the most the temporal cross-correlation of the information in addition to lineage information. 

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Additional resources for Analysis of Single-Cell Data: ODE Constrained Mixture Modeling and Approximate Bayesian Computation (BestMasters)

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As the use of MEs also provides information about variability in parameters we consider three scenarios: Scenario 1 Kinetic parameters are fixed across individual cells of a subpopulation. Scenario 2 Kinetic parameters vary little between individual cells of a subpopulation. Scenario 3 Kinetic parameters vary strongly between individual cells of a subpopulation. 7. 6: Schematic representation of a conversion process between species A and B, for which B can be measured. , 2014b). 1. For Scenarios 2 and 3 we assume that the parameters are log-normally distributed with mean μki and variance σk2i .

Thicker arrows, corresponding to the influence of TrkA:NGF on the Erk phosphorylation, and the higher abundance of TrkA in subpopulation 2, visualize the difference between the subpopulations. , 2014b). several ODE-MMs with RREs based on single-cell data of NGF-stimulated primary sensory neurons. 2). 2 Experimental Data and Problem Statement A goal of pain research is to fully understand the mechanism of pain sensitization. Therefore, it is studied how different conditions influence the pathways mediating painsensitivity.

To obtain estimates of the parameters we perform multi-start local optimization with 100 multi-starts. If the optimizer finds the same (possibly local) optimum less than 5 times, we increase the number of multi-starts and repeat the optimization. We restrict the kinetic parameters to the interval [10−10 , 1010 ], the variances to [10−1 , 10], the weights to [0, 1] and the additional parameter κ, which is used in H3 and H4 to [10−10 , 1010 ]. 1. 5. 1). 2 Assessment of ODE-MMs Using Novel Data for NGF-Induced Erk Signaling Er Erk Erk Er Er Er Erk Er Er Er Erk Trk Trk TrkA NG F Trk NGF F NG Trk Trk NGF N Trk Trk T kA A NG Trk A NG N FF pErrk pEr pErk pEr condition 2 subpop.

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