Dissertation/Thesis Abstract

A web semantic for SBML merge
by Thavappiragasam, Mathialakan, M.S., University of South Dakota, 2014, 86; 1566784
Abstract (Summary)

The manipulation of XML based relational representations of biological systems (BioML for Bioscience Markup Language) is a big challenge in systems biology. The needs of biologists, like translational study of biological systems, cause their challenges to become grater due to the material received in next generation sequencing. Among these BioML's, SBML is the de facto standard file format for the storage and exchange of quantitative computational models in systems biology, supported by more than 257 software packages to date. The SBML standard is used by several biological systems modeling tools and several databases for representation and knowledge sharing. Several sub systems are integrated in order to construct a complex bio system. The issue of combining biological sub-systems by merging SBML files has been addressed in several algorithms and tools. But it remains impossible to build an automatic merge system that implements reusability, flexibility, scalability and sharability. The technique existing algorithms use is name based component comparisons. This does not allow integration into Workflow Management System (WMS) to build pipelines and also does not include the mapping of quantitative data needed for a good analysis of the biological system. In this work, we present a deterministic merging algorithm that is consumable in a given WMS engine, and designed using a novel biological model similarity algorithm. This model merging system is designed with integration of four sub modules: SBMLChecker, SBMLAnot, SBMLCompare, and SBMLMerge, for model quality checking, annotation, comparison, and merging respectively. The tools are integrated into the BioExtract server leveraging iPlant collaborative resources to support users by allowing them to process large models and design work flows. These tools are also embedded into a user friendly online version SW4SBMLm.

Indexing (document details)
Advisor: Gnimpieba, Etienne
Commitee: Goodman, Douglas, Lushbough, Carol, Mabee, Paula
School: University of South Dakota
Department: Computer Science
School Location: United States -- South Dakota
Source: MAI 53/06M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Bioinformatics, Computer science
Keywords: Model annotation, Model comparison, Model evaluation, Model merging, Sbml, String similarity
Publication Number: 1566784
ISBN: 9781321256550
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