Data To Model - TR&D 4 Need to relate relative spatiotemporal fluorescence changes to species concentrations. – facilitates using experimental imaging.

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Presentation transcript:

Data To Model - TR&D 4 Need to relate relative spatiotemporal fluorescence changes to species concentrations. – facilitates using experimental imaging data as input to spatial models. – assess how well spatial model predictions correspond to experimental data. Need to handle moving geometry.

Data To Model - TR&D 4 Predicted Concentrations ROIs Image Storage Model Protocols Image Data Normalization Workflow Steady State Conditions Predicted Fluorescence Steady State Concentrations Predicted ROI Data Predicted Fluorescence Predicted ROI Data Compare ROI data and model predictions Initial Concentrations Geometry Time Varying Data Steady State ROI Data

Store and manage experimental imaging data and image processing/normalization workflow. (provenance and reusability). ROI manager leveraging FRAP 2D drawing tool and existing. Simulation automatically compute statistics over ROIs. Geometry Importer, remember the geometric transformations for registering 2D time series data. Simulated Fluorescence with PSF and all states of flurophores. Analyze time-course data and simulation results together. Provide for parameter scans Aim 1: Enable the use of spatial data in modeling. (DBPs: Pollard, Haugh, Mayer, Yi Wu, Tuzel, Iyengar) Image Storage ROIs Geometry

Aim 2: Develop tools to create data-driven initial conditions and estimate steady state. (Pollard, Haugh, Mayer, Yi Wu, Tuzel, Iyengar, Knecht) Dedicated tools to solve for initial conditions consistent with steady state and with constraints from experimental data (application-specific “basal conditions”). – Reduce storage, significant speedup for nonuniform steady state. – Automate ODE approximation for a uniform steady state. Link time varying simulations to the steady state – Develop separate transient protocols (events)

Aim 3: Provide support for time-varying geometries and multiscale geometry. (Pollard, Haugh, Mayer, Wolgemuth, Lederer, Iyengar, McCulloch) Cell motion kinematics (time varying shapes and velocities from data) – Integrated support for cell image registration over time (itk and dedicated tools such as elastix) Simple tools for metrics such as velocity of translation and rotation, and volume change. Parametric model for boundary velocity (edges) Parametric model for bulk velocity (intensity based).