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Virginia Tech

JigCell Model Connector: Building Large Molecular Network Models from Components

Abstract

dc:description.abstract

The ever-growing size and complexity of molecular network models makes them difficult to construct and understand. Modifying a model that consists of tens of reactions is no easy task. Attempting the same on a model containing hundreds of reactions can seem nearly impossible. We present the JigCell Model Connector, a software tool that supports large-scale molecular network modeling. Our approach to developing large models is to combine together smaller models, making the result easier to comprehend. At the base, the smaller models (called modules) are defined by small collections of reactions. Modules connect together to form larger modules through clearly defined interfaces, called ports. In this work, we enhance the port concept by defining different types of ports. Not all modules connect together the same way, therefore multiple connection options need to exist.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science and Applications
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Jones, Thomas Carroll Jr.
Chairs dc:contributor.committeechair
  • Shaffer, Clifford A.
  • Tyson, John J.
Committee members dc:contributor.committeemember
  • Hoops, Stefan
  • Watson, Layne T.

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:11726
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/78277

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Jones, Thomas Carroll Jr.. JigCell Model Connector: Building Large Molecular Network Models from Components. masters thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78277