Scalable computational architecture for integrating biological pathway models

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Biological Engineering Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Shiva, V. A

Advisor dc:contributor.advisor

• C. Forbes Dewey, Jr.

• Biological Engineering Division.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/42384

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/42384