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A PARALLEL COMPUTATION FRAMEWORK FOR EONS SYNAPTIC MODELING PLATFORM FOR PARAMETER OPTIMIZATION AND DRUG DISCOVERY
by
Sushmita Lakshmi Allam
__________________________________________________________
A Thesis Presented to the
FACULTY OF THE USC VITERBI SCHOOL OF ENGINEERING
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOMEDICAL ENGINEERING)
August 2008
Copyright 2008 Sushmita Lakshmi Allam
Object Description
| Title | A parallel computation framework for EONS synaptic modeling platform for parameter optimization and drug discovery |
| Author | Allam, Sushmita Lakshmi |
| Author email | sushmita.allam@gmail.com; allam@usc.edu |
| Degree | Master of Science |
| Document type | Thesis |
| Degree program | Biomedical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-06-26 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-08-08 |
| Advisor (committee chair) | Baudry, Michel |
| Advisor (committee member) |
Berger, Theodore W. D'Argenio, David Z. |
| Abstract | EONS modeling platform is a resourceful learning and research tool to study the mechanisms underlying the non–linear dynamics of synaptic transmission with the aid of mathematical models. Mathematical modeling of information processing in CNS pathways, in particular modeling of molecular events and synaptic dynamics, have not been extensively developed owing to the complex computations involved in integrating a multitude of parameters. In this paper, we discuss the development of a strategy to adapt the EONS synaptic modeling platform to a multi-node environment using a parallel computational framework to compute data intensive long simulations in a shorter time frame. We describe how this strategy can be applied to (i) determine the optimal values of the numerous parameters required for fitting experimental data, (ii) determine the impact of all parameters on various aspects of synaptic transmission (under normal conditions or conditions mimicking pathological conditions) and (iii) study the effects of exogenous molecules on both healthy and pathological synaptic models. |
| Keyword | synaptic modeling; parallel computation; cluster; node; CNS mathematical modeling; XML |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1567 |
| Contributing entity | University of Southern California |
| Rights | Allam, Sushmita Lakshmi |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@dots.usc.edu |
| Filename | etd-Allam-2305 |
| Archival file | uscthesesreloadpub_Volume32/etd-Allam-2305.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@dots.usc.edu |
| Full text | A PARALLEL COMPUTATION FRAMEWORK FOR EONS SYNAPTIC MODELING PLATFORM FOR PARAMETER OPTIMIZATION AND DRUG DISCOVERY by Sushmita Lakshmi Allam __________________________________________________________ A Thesis Presented to the FACULTY OF THE USC VITERBI SCHOOL OF ENGINEERING UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE (BIOMEDICAL ENGINEERING) August 2008 Copyright 2008 Sushmita Lakshmi Allam |
