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  1. Stochastic, Spatial and Concurrent Biological Processes Modeling Yifei Bao, Philippe Bidinger, Eduardo Bonelli, Vishakha Sharma, Justin Sousa, and Peter ZafonteAdvisor: Adriana B. CompagnoniDepartment of Computer Science, Schaefer School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ 07030 Graduate Student Research Conference October 6, 2010 ddd Introduction We define and implement a language for the stochastic simulation of biological processes with spatial information, which is an extension of the SPiM (Stochastic Pi Machine) language. Simulations in SPiM assume that all processes are uniformly distributed in space, and interactions between processes are scheduled randomly based on concentrations and reaction rates. Consequently, it cannot accurately model reactions that do not occur in a homogeneous mixture. In order to address this limitation, our new language places mobile processes in 3D space, where processes can interact only if they are within communication distance. We apply our language to modeling a drug delivery nano-system in collaboration with Prof. Libera and Prof. Sukhishvili From CCBBME. Drug Delivery System Modeling 1. Drug Delivery System 2. Our Language -- Simulation • Background • Stochastic Pi Machine (SPiM) • Our Language • New Spatial Features • Process state includes spatial information • Each process has a position and three vectors that define its local system of coordinates • This state can be modified by application of affine maps (translation, rotation..) • Simulation of movement (translation, rotations) • Interactions may be conditioned by the distance between two molecules Ongoing work 1. New features (shapes) 2. Validation (correctness of simulation) 3. Improved performance of simulation algorithm 4. Drug delivery system modeling (controlled experiments)

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