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ucin1271708137.pdf (1.92 MB)
ETD Abstract Container
Abstract Header
Agent Based and Stochastic Simulations for Non-homogeneous Systems
Author Info
Karkutla, Raja K.
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1271708137
Abstract Details
Year and Degree
2010, MS, University of Cincinnati, Engineering : Computer Engineering.
Abstract
Biological simulators can be a great aid to the biologists. These produce results much faster than actual wet-lab experiments and help in enhancing the understanding of biological systems. But there has been not much success in creating a tool that considers Brownian motion and non-homogeneity and also gives the flexibility to model a biomolecular system with particles of different structures and characteristics. GridCell is the first stochastic tool that can handle non-homogeneity effectively by addressing the issues of crowding and localization. Stochastic tools are built on Gillespie’s major assumption that individual particles should not be tracked in order to maintain stochastic analysis. GridCell handles this by partitioning the space into voxels. But even GridCell fails in giving the biologist the flexibility of modeling each particle uniquely with different characteristics. The agent-based technique, while it doesn't adhere to Gillespie’s formulation, comes closest to solving this problem. It is a bottom-up approach that considers each particle important to the simulation and thus tracks the individual particles. It gives biologists the flexibility to model each particle distinctly. An agent-based tool previously created in our laboratory did not account for Brownian motion and could not be validated to model non-homogeneous systems accurately. The revised version presented here, ABMSim, can model the non-homogeneity. We compare GridCell with ABMSim and we conclude that ABMSim can accurately model non-homogeneous systems. It has been compared qualitatively and quantitatively to the stochastic tool GridCell, and the two tools have produced similar results.
Committee
Carla Purdy, C, PhD (Committee Chair)
Ali Minai, PhD (Committee Member)
Wen Ben Jone, PhD (Committee Member)
Pages
116 p.
Subject Headings
Bioinformatics
Keywords
agent based model
;
stochastic
;
non homogeneous
;
biology
;
ABMSim
;
GridCell
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Citations
Karkutla, R. K. (2010).
Agent Based and Stochastic Simulations for Non-homogeneous Systems
[Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1271708137
APA Style (7th edition)
Karkutla, Raja.
Agent Based and Stochastic Simulations for Non-homogeneous Systems.
2010. University of Cincinnati, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1271708137.
MLA Style (8th edition)
Karkutla, Raja. "Agent Based and Stochastic Simulations for Non-homogeneous Systems." Master's thesis, University of Cincinnati, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1271708137
Chicago Manual of Style (17th edition)
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Document number:
ucin1271708137
Download Count:
668
Copyright Info
© 2010, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.