Mining bio-models for synthetic biology design

Engineering of microbes for various applications require lots of prior information. Bio Models database (https://www.ebi.ac.uk/biomodels/) has become a rich resource in which it captures many possible biochemical reactions in a form of mathematical models. It will be extremely useful to be able to m...

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Bibliographic Details
Main Author: Phang, Kevin Kai Siang
Other Authors: Poh Chueh Loo
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/68372
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Institution: Nanyang Technological University
Language: English
Description
Summary:Engineering of microbes for various applications require lots of prior information. Bio Models database (https://www.ebi.ac.uk/biomodels/) has become a rich resource in which it captures many possible biochemical reactions in a form of mathematical models. It will be extremely useful to be able to mine the models for known reactions whenever someone needs to design a new biological system. The aim of this project is to develop an algorithm to search and mine bio-models. The final product is able to extract relevant information from any bio-model file and present all critical data such as species, parameters, rules, reactions, events and rate equations in a readable manner. Display options are available to the user if he wishes to view the model in its original format (for accuracy checking against the respective annotated PDF file) or translated form. From the derived rate equation results window, users can examine the entire reaction pathway that a species is involved in and easily distinguish if the component is consumed or produced in the respective reactions. Users are also able to search for all reaction pathways between two specified molecules. The algorithm is capable of combining information from two or more bio-models and merging overlapping data. We hope that our work is able to enhance readability and usability for individuals or institutions utilizing bio-models on a large scale in their research.