In the first funding phase, the Modeling Initiative constructed a number of relational and biophysical models ofmechanics and molecular phenomena related to cell migration and started to develop migration relatedcapabilities within the Virtual Cell (VC) software. This activity can be considered as the last step in thereductionism agenda - in silico reconstitution of a simplified motile system using mathematical representationcombining biological knowledge and hypotheses, with determination of the consequences of these hypothesesfacilitated beyond human reasoning by means of computer-generated numerical calculations. These modelsand software development enabled the exciting possibility to make a large, critical step in our quantitativeunderstanding of cell migration from the point of view of systems biology. The models will be standardized fromthe technical point of view, integrated, comprehensive and predictive. A crucial feature of our endeavor,absolutely required for validating such models and using them for hypothesis prediction-test efforts, is that nomodeling is undertaken absent direct input from experimental collaborators. We will describe below themechanism by which this requirement will be consistently met.The Modeling Initiative will investigate migration mechanisms at the systems-level with a long term goalof developing a comprehensive model of cell migration. This model will have a modular character combiningdeterministic and stochastic components. Our approach is to develop models for each of the componentprocesses that drive cell migration, e.g.,development of polarity, protrusion,adhesion, and contraction and rearrelease, and then integrate them into acomprehensive model. For each of theseprocesses, a 'Process Team' that includesboth computational biologists andexperimental biologists (in a few cases,these capabilities reside within the samelaboratory ), will work together to developa 'Process Model' capable of capturingdynamic behavior in terms of molecularproperties (protein levels, states,locations, and activities). It is through thiscollaborative team that data will beproduced, analyzed, and modelediteratively with a goal of developingadditional data from model predictionsand using these data to refine the models.
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