Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.660232
Title: Visualising and exploring linked functional genomic data sets in the Yeast Exploration Tool Integrator (YETI)
Author: Orton, Richard J.
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2006
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Abstract:
This PhD project is split into two parts: (1) The development of the Yeast Exploration Tool Integrator (YETI), a novel bioinformatics tool for the integrated visualisation and analysis of S. cerevisiae functional genomic data sets; and (2) Using YETI for data analysis purposes. Part 1: YETI consists of a MySQL database for the storage and management of data and a Java program for visualisation and analysis. YETI uses publicly available data from both online databases and published scientific studies to populate its own database and scripts have been written to automatically retrieve and process all relevant data to keep the database up-to-date. YETI consists of four inter linked sections: (1) A Genome Section for the informative display of the S. cerevisiae genome, its chromosomes, known and predicted genes and associated annotations; (2) A Transcriptome Section for the integration, visualisation and analysis of gene expression microarray data; (3) A Proteome Section for the effective visualisation of protein-­protein interactions on a dynamic graphical panel; and (4) An Analysis Section providing a graphical interface to the database with a complex query search system. Part 2: A number of additional data analysis tools have been developed for use in conjunction with YETI. These tools have been used for the statistical analyses of individual data sets and for genome scale correlation analysis between data sets: 1) Genome vs Proteome: investigating if genes located near each other on the genome result in proteins that interact together in the cell. 2) Genome vs Transcriptome: investigating if genes located near each other on the genome are co-expressed under a number of different conditions. 3) Transcriptome vs Proteome: investigating if genes that are co-expressed under a number of different conditions result in proteins that interact together in the cell.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.660232  DOI: Not available
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