2026-09-19T11:35:09Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/423842022-01-13T07:53:48Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
C. Forbes Dewey, Jr.
Shiva, V. A
Massachusetts Institute of Technology. Biological Engineering Division.
Massachusetts Institute of Technology. Department of Biological Engineering
2008-09-03T15:30:28Z
2008-09-03T15:30:28Z
2007
2007
http://hdl.handle.net/1721.1/42384
234507495
Thesis (Ph. D.)--Massachusetts Institute of Technology, Biological Engineering Division, 2007.
MIT Institute Archives copy: DVD inserted in pocket on p. [3] of cover on v. 1.
"c2007"--p. ii.
Includes bibliographical references (v. 2, leaves 292-302).
A grand challenge of systems biology is to model the cell. The cell is an integrated network of cellular functions. Each cellular function, such as immune response, cell division, metabolism or apoptosis, is defined by an interconnected ensemble of biological pathways. Modeling the cell or even one cellular function requires a computational architecture that integrates multiple biological pathway models in a scalable manner while ensuring minimal effort to maintain the resulting integrated model. Scalable is defined as the ease in which more and more biological pathway models can be integrated. Current architectures for integrating biological pathway models are primarily monolithic and involve combining each biological pathway model's software source code to build one large monolithic model that executes on a single computer. Such architectures are not scalable for modeling complex cellular functions or the whole cell. We present Cytosolve, a new computational architecture that integrates a distributed ensemble of biological pathway models and computes solutions in a parallel manner while offering ease of maintenance of the integrated model. The individual biological pathway models can be represented in SBML, CellML or in any number of formats. The EGFR model of Kholodenko with known solutions is used to compare the Cytosolve solution and computational times with a known monolithic approach. A new integrative model of the interferon (IFN) response to virus infection is developed using Cytosolve. Each model within the integrated model, spans different time scales, is created by different authors from four countries and three continents across different disciplines, is written in different software codes, and is built on different hardware platforms.
(cont.) A new quantitative methodology and formalism is then derived for evaluating different types of monolithic and distributed architectures for integrating biological pathway models. As more biological pathway models develop in a disparate and decentralized manner, the Cytosolve architecture offers a unique platform to build and test complex models of cellular function, and eventually the whole cell.
by V.A. Shiva Ayyadurai.
Ph.D.
2 v. (xvii, 303 leaves)
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Biological Engineering Division.
Scalable computational architecture for integrating biological pathway models
IFN response to virus infection
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>A grand challenge of systems biology is to model the cell. The cell is an integrated network of cellular functions. Each cellular function, such as immune response, cell division, metabolism or apoptosis, is defined by an interconnected ensemble of biological pathways. Modeling the cell or even one cellular function requires a computational architecture that integrates multiple biological pathway models in a scalable manner while ensuring minimal effort to maintain the resulting integrated model. Scalable is defined as the ease in which more and more biological pathway models can be integrated. Current architectures for integrating biological pathway models are primarily monolithic and involve combining each biological pathway model's software source code to build one large monolithic model that executes on a single computer. Such architectures are not scalable for modeling complex cellular functions or the whole cell. We present Cytosolve, a new computational architecture that integrates a distributed ensemble of biological pathway models and computes solutions in a parallel manner while offering ease of maintenance of the integrated model. The individual biological pathway models can be represented in SBML, CellML or in any number of formats. The EGFR model of Kholodenko with known solutions is used to compare the Cytosolve solution and computational times with a known monolithic approach. A new integrative model of the interferon (IFN) response to virus infection is developed using Cytosolve. Each model within the integrated model, spans different time scales, is created by different authors from four countries and three continents across different disciplines, is written in different software codes, and is built on different hardware platforms.</Abstract>
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